For developers working in Windows environments, Git Bash offers a powerful bridge between the Unix command line world and Windows operating systems. This guide will walk you through essential Git Bash commands, practical workflows, and time-saving techniques that will transform how you interact with your code repositories.
Git Bash serves as a command-line terminal for Windows users that combines Git functionality with the Unix Bash shell environment. Unlike the standard Windows Command Prompt, Git Bash provides access to both Git commands and Unix utilities, creating a consistent environment across different operating systems.
At its core, Git Bash offers:
For Windows developers, Git Bash eliminates the barrier between operating systems, providing the same powerful command-line tools that macOS and Linux users enjoy. Rather than switching contexts between different command interfaces, Git Bash creates a unified experience.
Before diving into commands, let's ensure your Git Bash environment is properly configured.
When using Git for the first time, set up your identity:
# Set your username
git config --global user.name "Your Name"
# Set your email
git config --global user.email "youremail@example.com"
# Verify your settings
git config --list
Make Git Bash your own with these customizations:
# Enable colorful output
git config --global color.ui auto
# Set your preferred text editor
git config --global core.editor "code --wait" # For VS Code
For a more informative prompt, create or edit your .bash_profile file to show your current branch:
# Add this to your .bash_profile
parse_git_branch() {
git branch 2> /dev/null | sed -e '/^[^*]/d' -e 's/* \(.*\)/(\1)/'
}
export PS1="\[\033[36m\]\u\[\033[m\]@\[\033[32m\]\h:\[\033[33;1m\]\w\[\033[m\]\[\033[32m\]\$(parse_git_branch)\[\033[m\]$ "
Git Bash's power begins with basic file system navigation and management.
# Show current directory
pwd
# List files and directories
ls
ls -la # Show hidden files and details
# Change directory
cd project-folder
cd .. # Go up one level
cd ~ # Go to home directory
cd /c/ # Access C: drive
# Create a new directory
mkdir new-project
# Create a new file
touch README.md
# Copy files
cp original.txt copy.txt
cp -r source-folder/ destination-folder/ # Copy directory
# Move or rename files
mv oldname.txt newname.txt
mv file.txt /path/to/destination/
# Delete files and directories
rm unwanted.txt
rm -rf old-directory/ # Be careful with this!
# View file content
cat config.json
# View file with pagination
less large-file.log
# Search for text in files
grep "function" *.js
grep -r "TODO" . # Search recursively in current directory
These commands form the foundation of Git operations in your daily workflow.
# Initialize a new repository
git init
# Clone an existing repository
git clone https://github.com/username/repository.git
# Clone to a specific folder
git clone https://github.com/username/repository.git custom-folder-name
# Check repository status
git status
# Add files to staging area
git add filename.txt # Add specific file
git add . # Add all changes
git add *.js # Add all JavaScript files
git add src/ # Add entire directory
# Commit changes
git commit -m "Add user authentication feature"
# Amend the last commit
git commit --amend -m "Updated message"
# View commit history
git log
# Compact view of history
git log --oneline
# Graph view with branches
git log --graph --oneline --decorate
# View changes in a commit
git show commit-hash
# View changes between commits
git diff commit1..commit2
Branching is where Git's power truly shines, allowing parallel development streams.
# List all branches
git branch # Local branches
git branch -r # Remote branches
git branch -a # All branches
# Create a new branch
git branch feature-login
# Create and switch to a new branch
git checkout -b feature-payment
# Switch branches
git checkout main
# Rename a branch
git branch -m old-name new-name
# Delete a branch
git branch -d feature-complete
git branch -D feature-broken # Force delete
# Merge a branch into current branch
git merge feature-complete
# Merge with no fast-forward (creates a merge commit)
git merge --no-ff feature-login
# Rebase current branch onto another
git rebase main
# Interactive rebase to clean up commits
git rebase -i HEAD~5
Connect your local work with remote repositories for collaboration.
# List remote repositories
git remote -v
# Add a remote
git remote add origin https://github.com/username/repo.git
# Change remote URL
git remote set-url origin https://github.com/username/new-repo.git
# Remove a remote
git remote remove upstream
# Download changes without merging
git fetch origin
# Download and merge changes
git pull origin main
# Upload local changes
git push origin feature-branch
# Set up branch tracking
git branch --set-upstream-to=origin/main main
Save precious keystrokes with Git aliases and Bash shortcuts.
Add these to your .gitconfig file:
[alias]
# Status, add, and commit shortcuts
s = status
a = add
aa = add --all
c = commit -m
ca = commit --amend
# Branch operations
b = branch
co = checkout
cob = checkout -b
# History viewing
l = log --oneline --graph --decorate --all
ld = log --pretty=format:"%C(yellow)%h%Cred%d\\ %Creset%s%Cblue\\ [%cn]" --decorate
# Useful combinations
save = !git add --all && git commit -m 'SAVEPOINT'
undo = reset HEAD~1 --mixed
wipe = !git add --all && git commit -qm 'WIPE SAVEPOINT' && git reset HEAD~1 --hard
Add these to your .bash_profile or .bashrc:
# Quick status check
alias gs='git status'
# Branch management
alias gb='git branch'
alias gba='git branch -a'
alias gbd='git branch -d'
# Checkout shortcuts
alias gco='git checkout'
alias gcb='git checkout -b'
alias gcm='git checkout main'
# Pull and push simplified
alias gpl='git pull'
alias gps='git push'
alias gpom='git push origin main'
# Log visualization
alias glog='git log --oneline --graph --decorate'
alias gloga='git log --oneline --graph --decorate --all'
Level up your Git Bash skills with these powerful techniques.
# Save changes temporarily
git stash
# Save with a description
git stash push -m "Work in progress for feature X"
# List all stashes
git stash list
# Apply most recent stash
git stash apply
# Apply specific stash
git stash apply stash@{2}
# Apply and remove from stash list
git stash pop
# Remove a stash
git stash drop stash@{0}
# Clear all stashes
git stash clear
# Search commit messages
git log --grep="bug fix"
# Find who changed a line
git blame filename.js
# Find when a function was added/removed
git log -L :functionName:filename.js
# Find branches containing a commit
git branch --contains commit-hash
# Find all commits that modified a file
git log -- filename.txt
# Cherry-pick a commit
git cherry-pick commit-hash
# Revert a commit
git revert commit-hash
# Interactive rebase for cleanup
git rebase -i HEAD~5
# View reflog (history of HEAD changes)
git reflog
# Reset to a previous state
git reset --soft HEAD~3 # Keep changes staged
git reset --mixed HEAD~3 # Keep changes unstaged
git reset --hard HEAD~3 # Discard changes (careful!)Git Bash excels at solving common Git predicaments.
# Forgot to add a file to commit
git add forgotten-file.txt
git commit --amend --no-edit
# Committed to wrong branch
git branch correct-branch # Create the right branch
git reset HEAD~ --soft # Undo the commit but keep changes
git stash # Stash the changes
git checkout correct-branch
git stash pop # Apply changes to correct branch
git add . # Stage changes
git commit -m "Commit message" # Commit to correct branch
# When merge conflict occurs
git status # Check which files have conflicts
# After manually resolving conflicts
git add resolved-file.txt
git commit # Completes the merge
For more complex conflicts:
# Use merge tool
git mergetool
# Abort a problematic merge
git merge --abort
# Find deleted commits with reflog
git reflog
# Restore lost commit
git checkout commit-hash
# Create branch from detached HEAD
git checkout -b recovery-branch
While graphical Git clients are convenient, Git Bash provides superior capabilities in several scenarios:
Scenario: Cleanup branches after sprint completion
GUI approach: Manually select and delete each branch - tedious and error-prone.
Git Bash solution:
# Delete all local branches that have been merged to main
git checkout main
git branch --merged | grep -v "main" | xargs git branch -d
Scenario: Find who introduced a bug and when
GUI approach: Scroll through commit history hoping to spot the culprit.
Git Bash solution:
# Find when a line was changed
git blame -L15,25 problematic-file.js
# Find commits mentioning the feature
git log --grep="feature name"
# Find commits that changed specific functions
git log -p -S "functionName"
Scenario: Standardize commit formatting for team
GUI approach: Distribute written guidelines and hope team follows them.
Git Bash solution:
# Set up a commit template
git config --global commit.template ~/.gitmessage
# Create ~/.gitmessage with your template
# Then add a pre-commit hook to enforce standards
These examples demonstrate how Git Bash can handle complex scenarios more efficiently than GUI tools, especially for batch operations, deep repository analysis, and customized workflows.
Git Bash provides a Unix-like shell environment on Windows, including Bash commands (like grep, ls, and cd) that work differently from their CMD equivalents. It also comes pre-loaded with Git commands and supports Unix-style paths using forward slashes, making it more consistent with macOS and Linux environments.
While GUI clients are user-friendly, Git Bash offers powerful capabilities for complex operations, scripting, and automation that most GUIs can't match. Even if you primarily use a GUI, learning Git Bash gives you a fallback for situations where the GUI is insufficient or unavailable.
Windows: Download Git for Windows from git-scm.com, which includes Git Bash.
macOS: Git Bash isn't necessary since macOS already has a Unix-based Terminal. Install Git via Homebrew with brew install git.
Linux: Similarly, Linux distributions have native Bash terminals. Install Git with your package manager (e.g., apt-get install git for Ubuntu).
No! Git Bash provides a full Bash shell environment. You can use it for any command-line tasks, including file management, text processing, and running scripts—even in projects that don't use Git.
Set up credential storage with:
# Cache credentials for 15 minutes
git config --global credential.helper cache
# Store credentials permanently
git config --global credential.helper store
# Use Windows credential manager
git config --global credential.helper wincred
Yes, you can set up SSH keys for different accounts and create a config file to specify which key to use for which repository. This allows you to manage multiple accounts without constant credential switching.
By mastering Git Bash commands, you'll gain powerful tools that extend far beyond basic version control. The command line gives you precision, automation, and deep insight into your repositories that point-and-click interfaces simply can't match. Start with the basics, gradually incorporate more advanced commands, and soon you'll find Git Bash becoming an indispensable part of your development workflow.
Whether you're resolving complex merge conflicts, automating repetitive tasks, or diving deep into your project's history, Git Bash provides the tools you need to work efficiently and effectively. Embrace the command line, and watch your productivity soar.
Software engineering is a vast field, so much so that most people outside the tech world don’t realize just how many roles exist within it.
To them, software development is just about "coding," and they may not even know that roles like Quality Assurance (QA) testers exist. DevOps might as well be science fiction to the non-technical crowd.
One such specialized niche within software engineering is artificial intelligence (AI). However, an AI engineer isn’t just a developer who uses AI tools to write code. AI engineering is a discipline of its own, requiring expertise in machine learning, data science, and algorithm optimization.
In this post, we give you a detailed comparison.
An AI engineer specializes in designing, building, and optimizing artificial intelligence systems. Their work revolves around machine learning models, neural networks, and data-driven algorithms.
Unlike traditional developers, AI engineers focus on training models to learn from vast datasets and make predictions or decisions without explicit programming.
For example, an AI engineer building a skin analysis tool for a beauty app would train a model on thousands of skin images. The model would then identify skin conditions and recommend personalized products.
This role demands expertise in data science, mathematics, and more importantly—expertise in the industry. AI engineers don’t just write code—they enable machines to learn, reason, and improve over time.
A software engineer designs, develops, and maintains applications, systems, and platforms. Their expertise lies in programming, algorithms, and system architecture.
Unlike AI engineers, who focus on training models, software engineers build the infrastructure that powers software applications.
They work with languages like JavaScript, Python, and Java to create web apps, mobile apps, and enterprise systems.
For example, a software engineer working on an eCommerce mobile app ensures that customers can browse products, add items to their cart, and complete transactions seamlessly. They integrate APIs, optimize database queries, and handle authentication systems.
While some software engineers may use AI models in their applications, they don’t typically build or train them. Their primary role is to develop functional, efficient, and user-friendly software solutions.
Now that you have a gist of who they are, let’s understand how these roles differ. While both require programming expertise, their focus, skill set, and day-to-day tasks set them apart.
Software engineers work on designing, building, testing, and maintaining software applications across various industries. Their role is broad, covering everything from front-end and back-end development to cloud infrastructure and database management. They build web platforms, mobile apps, enterprise systems, and more.
AI engineers, however, specialize in creating intelligent systems that learn from data. Their focus is on building machine learning models, fine-tuning algorithms, and optimizing AI-powered solutions. Rather than developing entire applications, they work on AI components like recommendation engines, chatbots, and computer vision systems.
AI engineers need a deep understanding of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. They must be proficient in data science, statistics, and probability. Their role also demands expertise in neural networks, deep learning architectures, and data visualization. Strong mathematical skills are essential.
Software engineers, on the other hand, require a broader programming skill set. They must be proficient in languages like Python, Java, C++, or JavaScript. Their expertise lies in system architecture, object-oriented programming, database management, and API integration. Unlike AI engineers, they do not need in-depth knowledge of machine learning models.
Software engineering follows a structured development lifecycle: requirement analysis, design, coding, testing, deployment, and maintenance.
AI development, however, starts with data collection and preprocessing, as models require vast amounts of structured data to learn. Instead of traditional coding, AI engineers focus on selecting algorithms, training models, and fine-tuning hyperparameters.
Evaluation is iterative—models must be tested against new data, adjusted, and retrained for accuracy. Deployment involves integrating models into applications while monitoring for drift (when models become less effective over time).
Unlike traditional software, which works deterministically based on logic, AI systems evolve. Continuous updates and retraining are essential to maintain accuracy. This makes AI development more experimental and iterative than traditional software engineering.
AI engineers use specialized tools designed for machine learning and data analysis. They work with frameworks like TensorFlow, PyTorch, and Scikit-learn to build and train models. They also use data visualization platforms such as Tableau and Power BI to analyze patterns. Statistical tools like MATLAB and R help with modeling and prediction. Additionally, they rely on cloud-based AI services like Google Vertex AI and AWS SageMaker for model deployment.
Software engineers use more general-purpose tools for coding, debugging, and deployment. They work with IDEs like Visual Studio Code, JetBrains, and Eclipse. They manage databases with MySQL, PostgreSQL, or MongoDB. For version control, they use GitHub or GitLab. Cloud platforms like AWS, Azure, and Google Cloud are essential for hosting and scaling applications.
AI engineers collaborate closely with data scientists, who provide insights and help refine models. They also work with domain experts to ensure AI solutions align with business needs. AI projects often require coordination with DevOps engineers to deploy models efficiently.
Software engineers typically collaborate with other developers, UX designers, product managers, and business stakeholders. Their goal is to create a better experience. They engage with QA engineers for testing and security teams to ensure robust applications.
AI engineers focus on making systems learn from data and improve over time. Their solutions involve probabilities, pattern recognition, and adaptive decision-making. AI models can evolve as they receive more data.
Software engineers build deterministic systems that follow explicit logic. They design algorithms, write structured code, and ensure the software meets predefined requirements without changing behavior over time unless manually updated.
If you’re comparing AI engineers and software engineers, chances are you’ve also wondered—will AI replace software engineers? The short answer is no.
AI is making software delivery more effective and efficient. Large language models can generate code, automate testing, and assist with debugging. Some believe this will make software engineers obsolete, just like past predictions about no-code platforms and automated tools. But history tells a different story.
For decades, people have claimed that programmers would become unnecessary. From code generation tools in the 1990s to frameworks like Rails and Django, every breakthrough was expected to eliminate the need for engineers. Yet, demand for software engineers has only increased.
The reality is that the world still needs more software, not less. Businesses struggle with outdated systems and inefficiencies. AI can help write code, but it can’t replace critical thinking, problem-solving, or system design.
Instead of replacing software engineers, AI will make their their work more productive, efficient, and valuable.
With advancements in AI, the focus for software engineering teams should be on improving the quality of their outputs while achieving efficiency.
AI is not here to replace engineers but to enhance their capabilities—automating repetitive tasks, optimizing workflows, and enabling smarter decision-making. The challenge now is not just writing code but delivering high-quality software faster and more effectively.
This is where Typo comes in. With AI-powered SDLC insights, automated code reviews, and business-aligned investments, it streamlines the development process. It helps engineering teams ensure that the efforts are focused on what truly matters—delivering impactful software solutions.
Code rot, also known as software rot, refers to the gradual deterioration of code quality over time.
The term was more common in the early days of software engineering but is now often grouped under technical debt.
Research Gate has found that maintenance consumes 40-80% of a software project’s total cost, much of it due to code rot.
In this blog, we’ll explore its types, causes, consequences, and how to prevent it.
Code rot occurs when software degrades over time, becoming harder to maintain, modify, or scale. This happens due to accumulating inefficiencies and poor design decisions. If you don’t update the code often, you might also be prone to it. As a result of these inefficiencies, developers face increased bugs, longer development cycles, and higher maintenance costs.
Let’s say you’re building an eCommerce platform where each update introduces duplicate logic. This will create an unstructured and tangled codebase, which is a form of active code rot.
The same platform also has a legacy API integration. If not in use but still exist in the codebase, it’ll cause unnecessary dependencies and maintenance overhead. This is the form of dormant code rot.
Note that both types increase technical debt, slowing down future development.
The uncomfortable truth is that even your best code is actively decaying right now. And your development practices are probably accelerating its demise.
Here are some common causes of code rot:
Code that isn’t actively maintained tends to decay. Unpatched dependencies, minor bugs, or problematic sections that aren’t refactored — these small inefficiencies compound into major problems. Unmaintained code becomes outdated and difficult to work with.
Without proper documentation, developers struggle to understand original design decisions. Over time, outdated or missing documentation leads to incorrect assumptions and unnecessary workarounds. This lack of context results in code that becomes increasingly fragile and difficult to modify.
Quick fixes and rushed implementations create technical debt. While shortcuts may be necessary in the short term, they result in complex, fragile code that requires increasing effort to maintain. If left unaddressed, technical debt compounds, making future development error-prone.
A lack of uniform coding practices leads to a patchwork of different styles, patterns, and architectures. This inconsistency makes the codebase harder to read and debug, which increases the risk of defects.
Adapting code to new business requirements without refactoring leads to convoluted logic. Instead of restructuring for maintainability, developers often bolt on new functionality, which brings unnecessary complexity. Over time, this results in an unmanageable codebase.
If your development team is constantly struggling with unexpected bugs, slow feature development, or unclear logic, your code might be rotting.
Recognizing these early symptoms can help prevent long-term damage.
Code rot doesn’t just make development frustrating—it has tangible consequences that affect productivity, costs, and business performance.
Left unchecked, it can even lead to system failures. Here’s how code rot impacts different aspects of software development:
As code becomes more difficult to modify, even small changes require more effort. Developers spend more time debugging and troubleshooting rather than building new features. Over time, maintenance costs can surpass the original development costs.
A messy, inconsistent codebase forces developers to work around issues instead of solving problems efficiently. Poorly structured code increases cognitive load, leading to slower progress and higher turnover rates in development teams.
Unstable, outdated, or overly complex code increases the risk of crashes, data corruption, and security vulnerabilities. A single unpatched dependency or fragile module can bring down an entire application.
With a decaying codebase, adding new functionality becomes a challenge. Developers must navigate and untangle existing complexities, slowing down innovation and making it harder to stay agile. It only increases software delivery risks.
Code rot can lead to performance issues and inconsistent behavior in production. Users may experience slower load times, unresponsive interfaces, or frequent crashes, all of which negatively impact customer satisfaction and retention. Ignoring code rot directly impacts business success.
Code rot is inevitable, but it can be managed and reversed with proactive strategies. Addressing it requires a combination of better coding practices. Here’s how to fix code rot effectively:
Frequent code reviews help catch issues early, ensuring that poor coding practices don’t accumulate. Encourage team-wide adherence to clean code principles, and use automated tools to detect code smells and inefficiencies.
Instead of attempting a full system rewrite, adopt a continuous refactoring approach. Identify problematic areas and improve them gradually while implementing new features. This prevents disruption while steadily improving the codebase.
Outdated libraries and frameworks can introduce security risks and compatibility issues. Regularly update dependencies and remove unused packages to keep the codebase lean and maintainable.
Enforce consistent coding styles, naming conventions, and architectural patterns across the team. Use linters and formatting tools to maintain uniformity, reducing confusion and technical debt accumulation.
Well-documented code is easier to maintain and modify. Ensure that function descriptions, API references, and architectural decisions are clearly documented so future developers can understand and extend the code without unnecessary guesswork.
A robust test suite prevents regressions and helps maintain code quality. Implement unit, integration, and end-to-end tests to catch issues early, ensuring new changes don’t introduce hidden bugs.
Allocate engineering resources and dedicated time for refactoring and maintenance in each sprint. Technical debt should be addressed alongside feature development to prevent long-term decay.
Track engineering metrics like code complexity, duplication, cyclomatic complexity, and maintainability index to assess code health. Tools like Typo can help identify problem areas before they spiral into code rot.
By implementing these strategies, teams can reduce code rot and maintain a scalable and sustainable codebase.
Code rot is an unavoidable challenge, but proactive maintenance, refactoring, and standardization can keep it under control. Ignoring it leads to higher costs, slower development, and poor user experience.
To effectively track and prevent code rot, you can use engineering analytics platforms like Typo, which provide insights into code quality and team productivity.
Start optimizing your codebase with Typo today!
Speed matters in software development. Top-performing teams ship code in just two days, while many others lag at seven.
Software cycle time directly impacts product delivery and customer satisfaction - and it’s equally essential for your team's confidence.
CTOs and engineering leaders can’t reduce cycle time just by working faster. They must optimize processes, identify and eliminate bottlenecks, and consistently deliver value.
In this post, we’ll break down the key strategies to reduce cycle time.
Software cycle time measures how long it takes for code to go from the first commit to production.
It tracks the time a pull request (PR) spends in various stages of the pipeline, helping teams identify and address workflow inefficiencies.
Cycle time consists of four key components:
Software cycle time is a critical part of DORA metrics, complimenting others like deployment frequency, lead time for changes, and MTTR.
While deployment frequency indicates how often new code is released, cycle time provides insights into the efficiency of the development process itself.
Understanding and optimising software cycle time is crucial for several reasons:
Cycle time reflects how efficiently engineering teams work. For example, there are brands that reduce their PR cycle time with automated code reviews and parallel test execution. This change allows developers to focus more on feature development rather than waiting for feedback, resulting in faster, higher-quality code delivery.
Reducing cycle time accelerates product delivery, allowing teams to respond faster to market demands and customer feedback. Remember Amazon’s “two-pizza teams” model? It emphasizes small, independent teams with streamlined processes, enabling them to deploy code thousands of times a day. This agility helps Amazon quickly respond to customer needs, implement new features, and outpace competitors.
The ability to ship high-quality software quickly can set a company apart from competitors. Faster delivery means quicker innovation and better customer satisfaction. For example, Netflix’s use of chaos engineering and Service-Level Prioritized Load Shedding has allowed it to continuously improve its streaming service, roll out updates seamlessly, and maintain its market leadership in the streaming industry.
Cycle time is one aspect that engineering teams cannot overlook — apart from all the technical reasons, it also has psychological impact. If Cycle time is high, the productivity level further drops because of demotivation and procrastination.
Reducing cycle time is easier said than done. There are several factors that affect efficiency and workflow.
Reducing software cycle time requires a combination of technical improvements, process optimizations, and cultural shifts. Here are six actionable strategies to implement today:
Establish clear SLAs for review timelines—e.g., 48 hours for initial feedback. Use tools like GitHub’s code owners to automatically assign reviewers based on file ownership. Implement peer programming for critical features to accelerate feedback loops. Introduce a "reviewer rotation" system to distribute the workload evenly across the team and prevent bottlenecks.
Identify repetitive tasks such as testing, integration, and deployment. And then implement CI/CD pipelines to automate these processes. You can also use test parallelization to speed up execution and set up automatic triggers for deployments to staging and production environments. Ensure robust rollback mechanisms are in place to reduce the risk of deployment failures.
Break down silos by encouraging cross-functional collaboration between developers, QA, and operations. Adopt DevOps principles and use tools like Slack for real-time communication and Jira for task tracking. Schedule regular cross-team sync-ups, and document shared knowledge in Confluence to avoid communication gaps. Establish a "Definition of Ready" and "Definition of Done" to align expectations across teams.
Schedule dedicated time each sprint to address technical debt. One amazing cycle time reduction strategy is to categorise debt into critical, moderate, and low-priority issues and then focus first on high-impact areas that slow down development. Implement a policy where no new feature work is done without addressing related legacy code issues.
Track cycle time by analysing PR stages—coding, pickup, review, and merge. Use tools like Typo to visualise bottlenecks and benchmark team performance. Establish a regular cadence to review these engineering metrics and correlate them with other DORA metrics to understand their impact on overall delivery performance. If review time consistently exceeds targets, consider adding more reviewers or refining the review process.
A cluttered backlog leads to confusion and context switching. Use prioritization frameworks like MoSCoW or RICE to focus on high-impact tasks. Ensure stories are clear, with well-defined acceptance criteria. Regularly groom the backlog to remove outdated items and reassess priorities. You can also introduce a “just-in-time” backlog refinement process to prepare stories only when they're close to implementation.
Reducing software cycle time requires the right set of tools to streamline development workflows, automate processes, and provide actionable insights.
Here’s how key tools contribute to cycle time optimization:
GitHub and GitLab simplify version control, enabling teams to track code changes, collaborate efficiently, and manage pull requests. Features like branch protection rules, code owners, and merge request automation reduce delays in code reviews. Integrated CI/CD pipelines further streamline code integration and testing.
These CI/CD tools automate build, test, and deployment processes, reducing manual intervention, ensuring faster feedback loops and more effective software delivery. Parallel execution, pipeline caching, and pre-configured environments significantly cut down build times and prevent bottlenecks.
Typo provides in-depth insights into cycle time by analyzing Git data across stages like coding, pickup, review, and merge. It highlights bottlenecks, tracks team performance, and offers actionable recommendations for process improvement. By visualizing trends and measuring PR cycle times, Typo helps engineering leaders make data-driven decisions and continuously optimize development workflows.
In your next development project, if you do not want to feel that this is taking forever, follow these best practices:
Reducing software cycle time is critical for both engineering efficiency and business success. It directly impacts product delivery speed, market responsiveness, and overall team performance.
Engineering leaders should continuously evaluate processes, implement automation tools, and track cycle time metrics to streamline workflows and maintain a competitive edge.
And it all starts with accurate measurement of software cycle time.
Professional service organizations within software companies maintain a delivery success rate hovering in the 70% range.
This percentage looks good. However, it hides significant inefficiencies given the substantial resources invested in modern software delivery lifecycles.
Even after investing extensive capital, talent, and time into development cycles, missing targets on every third of projects should not be acceptable.
After all, there’s a direct correlation between delivery effectiveness and organizational profitability.
However, the complexity of modern software development - with its complex dependencies and quality demands - makes consistent on-time, on-budget delivery persistently challenging.
This reality makes it critical to master effective software delivery.
The Software Delivery Lifecycle (SDLC) is a structured sequence of stages that guides software from initial concept to deployment and maintenance.
Consider Netflix's continuous evolution: when transitioning from DVD rentals to streaming, they iteratively developed, tested, and refined their platform. All this while maintaining uninterrupted service to millions of users.
A typical SDLC has six phases:
Each phase builds upon the previous, creating a continuous loop of improvement.
Modern approaches often adopt Agile methodologies, which enable rapid iterations and frequent releases. This also allows organizations to respond quickly to market demands while maintaining high-quality standards.
Even the best of software delivery processes can have leakages in terms of engineering resource allocation and technical management. By applying these software delivery best practices, you can achieve effectiveness:
Effective project management requires systematic control over development workflows while maintaining strategic alignment with business objectives.
Modern software delivery requires precise distribution of resources, timelines, and deliverables.
Here’s what you should implement:
Quality assurance integration throughout the SDLC significantly reduces defect discovery costs.
Early detection and prevention strategies prove more effective than late-stage fixes. This ensures that your time is used for maximum potential helping you achieve engineering efficiency.
Some ways to set up robust a QA process:
Efficient collaboration accelerates software delivery cycles while reducing communication overhead.
There are tools and practices available that facilitate seamless information flow across teams.
Here’s how you can ensure the collaboration is effective in your engineering team:
Security integration throughout development prevents vulnerabilities and ensures compliance. Instead of fixing for breaches, it’s more effective to take preventive measures.
To implement strong security measures:
Scalable architectures directly impact software delivery effectiveness by enabling seamless growth and consistent performance even when the load increases.
Strategic implementation of scalable processes removes bottlenecks and supports rapid deployment cycles.
Here’s how you can build scalability into your processes:
CI/CD automation streamlines deployment processes and reduces manual errors. Now, there are pipelines available that are rapid, reliable software delivery through automated testing and deployment sequences. Integration with version control systems ensures consistent code quality and deployment readiness. This means there are less delays and more effective software delivery.
Effective software delivery requires precise measurement through carefully selected metrics. These metrics provide actionable insights for process optimization and delivery enhancement.
Here are some metrics to keep an eye on:
These metrics provide quantitative insights into delivery pipeline efficiency and help identify areas for continuous improvement.
The SDLC has multiple technical challenges at each phase. Some of them include:
Teams grapple with requirement volatility leading to scope creep. API dependencies introduce integration uncertainties, while microservices architecture decisions significantly impact system complexity. Resource estimation becomes particularly challenging when accounting for potential technical debt.
Design phase complications are around system scalability requirements conflicting with performance constraints. Teams must carefully balance cloud infrastructure selections against cost-performance ratios. Database sharding strategies introduce data consistency challenges, while service mesh implementations add layers of operational complexity.
Development phase issues leads to code versioning conflicts across distributed teams. Software engineers frequently face memory leaks in complex object lifecycles and race conditions in concurrent operations. Then there are rapid sprint cycles that often result in technical debt accumulation, while build pipeline failures occur from dependency conflicts.
Testing becomes increasingly complex as teams deal with coverage gaps in async operations and integration failures across microservices. Performance bottlenecks emerge during load testing, while environmental inconsistencies lead to flaky tests. API versioning introduces additional regression testing complications.
Deployment challenges revolve around container orchestration failures and blue-green deployment synchronization. Teams must manage database migration errors, SSL certificate expirations, and zero-downtime deployment complexities.
In the maintenance phase, teams face log aggregation challenges across distributed systems, along with memory utilization spikes during peak loads. Cache invalidation issues and service discovery failures in containerized environments require constant attention, while patch management across multiple environments demands careful orchestration.
These challenges compound through modern CI/CD pipelines, with Infrastructure as Code introducing additional failure points.
Effective monitoring and observability become crucial success factors in managing them.
Use software engineering intelligence tools like Typo to get visibility on precise performance of the teams, sprint delivery which helps you in optimizing resource allocation and reducing tech debt better.
Effective software delivery depends on precise performance measurement. Without visibility into resource allocation and workflow efficiency, optimization remains impossible.
Typo addresses this fundamental need. The platform delivers insights across development lifecycles - from code commit patterns to deployment metrics. AI-powered code analysis automates optimization, reducing technical debt while accelerating delivery. Real-time dashboards expose productivity trends, helping you with proactive resource allocation.
Transform your software delivery pipeline with Typo's advanced analytics and AI capabilities.
Smooth and reliable deployments are key to maintaining user satisfaction and business continuity. This is where DORA metrics play a crucial role.
Among these metrics, the Change Failure Rate provides valuable insights into how frequently deployments lead to failures. Hence, helping teams minimize disruptions in production environments.
Let’s read about CFR further!
In 2015, Gene Kim, Jez Humble, and Nicole Forsgren founded the DORA (DevOps Research and Assessment) team to evaluate and improve software development practices. The aim is to improve the understanding of how organizations can deliver faster, more reliable, and higher-quality software.
DORA metrics help in assessing software delivery performance based on four key (or accelerate) metrics:
While these metrics provide valuable insights into a team's performance, understanding CFR is crucial. It measures the effectiveness of software changes and their impact on production environments.
The Change Failure Rate (CFR) measures how often new deployments cause failures, glitches, or unexpected issues in the IT environment. It reflects the stability and reliability of the entire software development and deployment lifecycle.
It is important to measure the Change Failure Rate for various reasons:
Change Failure Rate calculation is done by following these steps:
Apply the formula:
CFR = (Number of Failed Changes / Total Number of Changes) * 100 to calculate the Change Failure Rate as a percentage.
For example, Suppose during a month:
Failed Changes = 2
Total Changes = 30
Using the formula: (2/30)*100 = 5
Therefore, the Change Failure Rate for that period is 6.67%.
An ideal failure rate is between 0% and 15%. This is the benchmark and standard that the engineering teams need to maintain. Low CFR equals stable, reliable, and well-tested software.
When the Change Failure Rate is above 15%, it reflects significant issues with code quality, testing, or deployment processes. This leads to increased system downtime, slower deployment cycles, and a negative impact on user experience.
Hence, it is always advisable to keep CFR as low as possible.
Follow the right steps to measure the Change Failure Rate effectively. Here’s how you can do it:
Clearly define what constitutes a ‘Change’ and a ‘Failure,’ such as service disruptions, bugs, or system crashes. Having clear metrics ensures the team is aligned and consistently collecting data.
Firstly, define the scope of change that needs to be included in CFR calculation. Besides this, include the details to be added for deciding the success or failure of changes. Have a Change Management System to track or log changes in a database. You can use tools like JIRA, GIT or CI/CD pipelines to automate and review data collection.
Understand the difference between Change Failure and Deployment Failure.
Deployment Failure: Failures that occur during the process of deploying code or changes to a production environment.
Change Failure: Failures that occur after the deployment when the changes themselves cause issues in the production environment.
This ensures that the team focuses on improving processes rather than troubleshooting unrelated issues.
Don’t analyze failures only once. Analyze trends continuously over different time periods, such as weekly, monthly, and quarterly. The trends and patterns help reveal recurring issues, prioritize areas for improvement, and inform strategic decisions. This allows teams to adapt and improve continuously.
DORA Metrics provide valuable insights into software development performance and identify high-level trends. However, they fail to capture the nuances such as the complexity of changes or severity of failures. Use them alongside other metrics for a holistic view. Also, ensure that these metrics are used to drive meaningful improvements rather than just for reporting purposes.
Various factors including team experience, project complexity, and organizational culture can influence the Change Failure Rate. These factors can impact both the failure frequency and effect of mitigation strategy. This allows you to judge failure rates in a broader context rather than only based on numbers.
Filter out the failures caused by external factors such as third-party service outages or hardware failure. This helps accurately measure CFR as external incidents can distort the true failure rate and mislead conclusions about your team’s performance.
Identify the root causes of failures and implement best practices in testing, deployment, and monitoring. Here are some effective strategies to minimize CFR:
Implement an automated testing strategy during each phase of the development lifecycle. The repeatable and consistent practice helps catch issues early and often, hence, improving code quality to a great extent. Ensure that the test results are also made accessible so they can have a clear focus on crucial aspects.
Small deployments in more frequent intervals make testing and detecting bugs easier. They reduce the risks of failures from deploying code to production issues as the issues are caught early and addressed before they become significant problems. Moreover, the frequent deployments provide quicker feedback to the team members and engineering leaders.
Continuous Integration and Continuous Deployment (CI/CD) ensures that code is regularly merged, tested, and deployed automatically. This reduces the deployment complexity and manual errors and allows teams to detect and address issues early in the development process. Hence, ensuring that only high-quality code reaches production.
Establishing a culture where quality is prioritized helps teams catch issues before they escalate into production failures. Adhering to best practices such as code reviews, coding standards, and refactoring continuously improves the quality of code. High-quality code is less prone to bugs and vulnerabilities and directly contributes to a lower CFR.
Real-time monitoring and alerting systems help teams detect issues early and resolve them quickly. This minimizes the impact of failures, improves overall system reliability, and provides immediate feedback on application performance and user experience.
Creating a learning culture within the development team encourages continuous improvement and knowledge sharing. When teams are encouraged to learn from past mistakes and successes, they are better equipped to avoid repeating errors. This involves conducting post-incident reviews and sharing key insights. This approach also fosters collaboration, accountability, and continuous improvement.
Since the definition of Failure is specific to teams, there are multiple ways this metric can be configured. Here are some guidelines on what can indicate a failure :
A deployment that needs a rollback or a hotfix
For such cases, any Pull Request having a title/tag/label that represents a rollback/hotfix that is merged to production can be considered a failure.
A high-priority production incident
For such cases, any ticket in your Issue Tracker having a title/tag/label that represents a high-priority production incident can be considered a failure.
A deployment that failed during the production workflow
For such cases, Typo can integrate with your CI/CD tool and consider any failed deployment as a failure.
To calculate the final percentage, the total number of failures is divided by the total number of deployments (this can be picked either from the Deployment PRs or from the CI/CD tool deployments).
Measuring and reducing the Change Failure Rate is a strategic necessity. It enables engineering teams to deliver stable software, leading to happier customers and a stronger competitive advantage. With tools like Typo, organizations can easily track and address failures to ensure successful software deployments.
Most companies treat software development costs as just another expense and are unsure how certain costs can be capitalized.
Recording the actual value of any software development process must involve recognizing the development process as a high-return asset.
That’s what software capitalization is for.
This article will answer all the what’s, why’s, and when’s of software capitalization.
Software capitalization is an accounting process that recognizes the incurred software development costs and treats them as long-term assets rather than immediate expenses. Typical costs include employee wages, third-party app expenses, consultation fees, and license purchases. The idea is to amortize these costs over the software’s lifetime, thus aligning expenses with future revenues generated by the software.
This process illustrates how IT development and accounting can seamlessly integrate. As more businesses seek to enhance operational efficiency, automating systems with custom software applications becomes essential. By capitalizing software, companies can select systems that not only meet their operational needs but also align accounting practices with strategic IT development goals.
In this way, software capitalization serves as a bridge between the tech and financial realms, ensuring that both departments work hand in hand to support the organization’s long-term objectives. This synergy reinforces the importance of choosing compatible systems that optimize both technological advancements and financial reporting.
Shifting a developed software’s narrative from being an expense to a revenue-generating asset comes with some key advantages:
Capitalization helps preserve profitability for the longer term by reducing the impact on the company’s expenses. That’s because you amortize intangible and tangible asset expenses, thus minimizing cash flow impact.
Capitalizing software development costs results in higher reported asset value and reduces short-term expenses, which ultimately improves your profitability metrics like net profit margin, ARR growth, and ROA (return on assets).
Software capitalization complies with the rules set by major accounting standards like ASC 350-40, U.S. GAAP, and IFRS and makes it easier for companies to undergo audits.
Here’s when it’s acceptable to capitalize software costs:
The software development stage starts when you receive funding and are in an active development phase. Here, you can capitalize on any cost directly related to development, considering the software is for internal use.
Example costs include interface designing, coding, configuring, installation, and testing.
For internal-use software like CRM, production automation, and accounting systems, consider the following:
If the software is intended for external use, then your costs can be capitalized when the software reaches the technical feasibility stage, i.e., when it’s viable. Example costs include coding, testing, and employee wages.
The software must be a probable candidate to generate consistent revenue for your company in the long run and considered an “asset.” For external use software, this can mean it possesses a selling and leasing expectation.
The overall software development costs must be accurately measurable. This way, you ensure that the capitalized amount reflects the software’s exact invested amount.
Ensure that all accounting procedures adhere to GAAP regulations, which provide the framework for accurately reporting and capitalizing software costs. This compliance underscores the financial integrity of your capitalization efforts.
By combining these criteria with a structured approach to expense and capital cost management, companies can effectively navigate the complexities of software capitalization, ensuring both compliance and financial clarity.
The five main costs you can capitalize for software are:
Direct costs that go into your active development phase can be capitalized. These include payroll costs of employees who were directly part of the software development, additional software purchase fees, and travel costs.
These costs include the ones incurred by the developers when working with external service providers. Examples include travel costs, technical support, outsourcing expenses, and more.
License fees can be capitalized instead of being treated as an expense. However, this can depend on the type of accounting standard. For example, GAAP’s terms state capitalization is feasible for one-time software license purchases where it provides long-term benefits.
When deciding whether to capitalize or expense software licenses, timing and the stage of the project play crucial roles. Generally, costs incurred during the preliminary and implementation stages are recorded as expenses. These stages include the initial planning and setup, where the financial outlay does not yet contribute directly to the creation of a tangible asset.
In contrast, during the development stage, many costs can be capitalized. This includes expenditures directly contributing to building and testing the software, as this stage is where the asset truly begins to take shape. Capitalization should continue until the project reaches completion and the software is either used internally or marketed externally.
Understanding these stages and criteria allows businesses to make informed decisions about their software investments, ensuring they align with accounting principles and maximize financial benefits.
Acquisition costs can be capitalized as assets, provided your software is intended for internal use.
Training and documentation costs are considered assets only if you’re investing in them during the development phase. Post-implementation, these costs turn into operating expenses and cannot be amortized.
Here are a few costs that do not qualify for software capitalization and are expensed:
Research and planning stages are categorized under the preliminary software development stage. These incurred costs are expensed and cannot be capitalized. The GAAP accounting standard, for example, states that an organization can begin to capitalize on costs only after completing these stages.
Post-implementation or the operational stage is the maintenance period after the software is fully deployed. Any costs, be it training, support, or other operational charges during this time are expensed as incurred.
Any costs related to software upgrades, modernization, or enhancements cannot be capitalized. For example, money spent on bug fixes, future modifications, and routine maintenance activities.
Below are the two most common accounting standards that state the eligibility criteria for software capitalization:
GAAP is a set of rules and procedures that organizations must follow while preparing their financial statements. These standards ensure accuracy and transparency in reporting across industries, including software.
IFRS is an alternative to GAAP and is used worldwide. Compared to GAAP, IFRS allows better capitalization of development costs, considering you meet every criterion, naturally making the standard more complex.
Software capitalization, from a financial perspective, can have the following aftereffects:
A company’s profit and loss (P&L) statement is an income report that shows the company’s overall expenses and revenues. So, if your company wishes to capitalize some of the software’s R&D costs, they are recognized as “profitable assets” instead of “losses,” so development can be amortized over a time period.
Software capitalization treats your development-related costs as long-term assets rather than incurred expenses. This means putting these costs on a balance sheet without recognizing the initial costs until you have a viable finished product that generates revenue. As a result, it delays paying taxes on those costs and leads to a bigger net income over that period.
This approach allows companies to manage their financial narratives better, demonstrating profitability and stability, which are crucial for growth and investment.
Although tax implications can be complex, capitalizing on software can often lead to tax deferral. That’s because amortization deductions are spread across multiple periods, reducing your company’s tax burden for the time being.
When a software project is canceled, one of the key financial implications revolves around capitalization. Here's what you need to know:
Understanding these consequences helps businesses make informed decisions about resource allocation and financial management when considering the fate of a software project.
✓ Specific identifiable project
✓ Intent to complete and use the software
✓ Technical feasibility demonstrated
✓ Expected future economic benefits
✓ Sufficient resources to complete project
✓ Ability to reliably measure development costs
Capitalize the entire $464,145 as an intangible asset, amortizing over 4 years.
Tracking R&D investments is a major part of streamlining software capitalization while leaving no room for manual errors. With Typo, you streamline this entire process by automating the reporting and management of R&D costs.
Typo’s best features and benefits for software capitalization include:
Typo transforms R&D from a cost center into a revenue-generating function by optimizing financial workflows and improving engineering efficiency, thus maximizing your returns on software development investments.
Capitalizing software costs allows tech companies to secure better investment opportunities by increasing profits legitimately.
Although software capitalization can be quite challenging, it presents massive future revenue potential.
With a tool like Typo, you rapidly maximize returns on software development investments with its automated capitalized asset reporting and real-time effort tracking.
Look, let's cut to the chase. As a software developer, you've probably heard about cyclomatic complexity, but maybe you've never really dug deep into what it means or why it matters. This guide is going to change that. We'll break down everything you need to know about cyclomatic complexity - from its fundamental concepts to practical implementation strategies.
Cyclomatic complexity is essentially a software metric that measures the structural complexity of your code. Think of it as a way to quantify how complicated your software's control flow is. The higher the number, the more complex and potentially difficult to understand and maintain your code becomes.
Imagine your code as a roadmap. Cyclomatic complexity tells you how many different paths or "roads" exist through that map. Each decision point, each branch, each conditional statement adds another potential route. More routes mean more complexity, more potential for bugs, and more challenging maintenance.
The classic formula for cyclomatic complexity is beautifully simple:
Where:
Alternatively, you can calculate it by counting decision points:
Decision points include:
Let's break down a code snippet:
Calculation:
Let's walk through a real-world scenario to demonstrate how complexity increases.
Cyclomatic Complexity: 1 (No decision points)
Cyclomatic Complexity: 3 (Two decision points)
Cyclomatic Complexity: 7-8 (Multiple nested conditions)
Most modern programming languages have tools to automatically calculate cyclomatic complexity:
Before (High Complexity):
After (Lower Complexity):
Typo’s automated code review tool identifies issues in your code and auto-fixes them before you merge to master. This means less time reviewing and more time for important tasks. It keeps your code error-free, making the whole process faster and smoother by optimizing complex methods, reducing cyclomatic complexity, and standardizing code efficiently.
Cyclomatic complexity isn't just a theoretical concept—it's a practical tool for writing better, more maintainable code. By understanding and managing complexity, you transform yourself from a mere coder to a software craftsman.
Remember: Lower complexity means:
Keep your code clean, your complexity low, and your coffee strong! 🚀👩💻👨💻
Pro Tip: Make complexity measurement a regular part of your code review process. Set team standards and continuously refactor to keep your codebase healthy.
Scope creep is one of the most challenging—and often frustrating—issues engineering managers face. As projects progress, new requirements, changing technologies, and evolving stakeholder demands can all lead to incremental additions that push your project beyond its original scope. Left unchecked, scope creep strains resources, raises costs, and jeopardizes deadlines, ultimately threatening project success.
This guide is here to help you take control. We’ll delve into advanced strategies and practical solutions specifically for managers to spot and manage scope creep before it disrupts your project. With detailed steps, technical insights, and tools like Typo, you can set boundaries, keep your team aligned, and drive projects to a successful, timely completion.
Scope creep can significantly impact projects, affecting resource allocation, team morale, and project outcomes. Understanding what scope creep is and why it frequently occurs provides a solid foundation for developing effective strategies to manage it.
Scope creep in projects refers to the gradual addition of project requirements beyond what was originally defined. Unlike industries with stable parameters, Feature projects often encounter rapid changes—emerging features, stakeholder requests, or even unanticipated technical complexities—that challenge the initial project boundaries.
While additional features can improve the end product, they can also risk the project's success if not managed carefully. Common triggers for scope creep include unclear project requirements, mid-project requests from stakeholders, and iterative development cycles, all of which require proactive management to keep projects on track.
Scope creep often results from the unique factors inherent to the industry. By understanding these drivers, you can develop processes that minimize their impact and keep your project on target.
Scope creep often results from several factors unique to the field:
These challenges make it essential for managers to recognize scope creep indicators early and develop robust systems to manage new requests and technical changes.
Identifying scope creep early is key to preventing it from derailing your project. By setting clear boundaries and maintaining consistent communication with stakeholders, you can catch scope changes before they become a problem.
The first step in minimizing scope creep is establishing a well-defined project scope that explicitly outlines deliverables, timelines, and performance metrics. In sprints, this scope must include technical details like software requirements, infrastructure needs, and integration points.
Frequent communication with stakeholders is crucial to ensure alignment on the project’s progress. Schedule periodic reviews to present progress, confirm objectives, and clarify any evolving requirements.
Integrate routine reviews into the project workflow to regularly assess the project’s alignment with its scope. Typo enables teams to conduct these reviews seamlessly, providing a comprehensive view of the project’s current state. This structured approach allows managers to address any adjustments or unexpected tasks before they escalate into significant scope creep issues.
Once scope creep has been identified, implementing specific strategies can help prevent it from escalating. With the following approaches, you can address new requests without compromising your project timeline or objectives.
One of the most effective ways to manage scope creep is to establish a formal change control process. A structured approach allows managers to evaluate each change request based on its technical impact, resource requirements, and alignment with project goals.
Communication breakdowns can lead to unnecessary scope expansion, especially in complex team environments. Use Typo’s Sprint Analysis to track project changes and real-time developments. This level of visibility gives stakeholders a clear understanding of trade-offs and allows managers to communicate the impact of requests, whether related to resource allocation, budget implications, or timeline shifts.
In Software development, feature prioritization can be a strategic way to handle evolving needs without disrupting core project objectives. When a high-priority change arises, use Typo to evaluate resource availability, timelines, and dependencies, making necessary adjustments without jeopardizing essential project elements.
Beyond basic strategies, specific tools and advanced techniques can further safeguard your IT project against scope creep. Leveraging project management solutions and rigorous documentation practices are particularly effective.
For projects, having a comprehensive project management tool can make all the difference. Typo provides robust tracking for timelines, tasks, and resources that align directly with project objectives. Typo also offers visibility into task assignments and dependencies, which helps managers monitor all project facets and mitigate scope risks proactively.
Documentation is vital in managing scope creep, especially in projects where technical requirements can evolve quickly. By creating a “single source of truth,” Typo enables the team to stay aligned, with full visibility into any shifts in project requirements.
Software projects benefit greatly from budget and time contingencies that allow for minor, unexpected adjustments. By pre-allocating resources for possible scope adjustments, managers have the flexibility to accommodate minor changes without impacting the project’s overall trajectory.
As scope adjustments occur, it’s important to maintain team morale and motivation. Empowering the team and celebrating their progress can help keep everyone focused and resilient.
Encouraging team members to communicate openly about their workload and project demands is crucial for maintaining productivity and morale.
Managing IT projects with scope creep can be challenging, so it’s essential to celebrate milestones and acknowledge team achievements.
Typo’s sprint analysis monitors scope creep to quantify its impact on the team’s workload and deliverables. It allows you to track and analyze your team’s progress throughout a sprint and helps you gain visual insights into how much work has been completed, how much work is still in progress, and how much time is left in the sprint. This information enables you to identify any potential problems early on and take corrective action.
Our sprint analysis feature uses data from Git and issue management tools to provide insights into how your team is working. You can see how long tasks are taking, how often they’re being blocked, and where bottlenecks are occurring. This information can help you identify areas for improvement and make sure your team is on track to meet their goals.
Effective management of scope creep in IT projects requires a balance of proactive planning, structured communication, and robust change management. With the right strategies and tools like Typo, managers can control project scope while keeping the team focused and aligned with project goals.
If you’re facing scope creep challenges, consider implementing these best practices and exploring Typo’s project management capabilities. By using Typo to centralize communication, track progress, and evaluate change requests, IT managers can prevent scope creep and lead their projects to successful, timely completion.
Are your code reviews fostering constructive discussions or stuck in endless cycles of revisions?
Let’s change that.
In many development teams, code reviews have become a necessary but frustrating part of the workflow. Rather than enhancing collaboration and improvement, they often drag on, leaving developers feeling drained and disengaged.
This inefficiency can lead to rushed releases, increased bugs in production, and a demotivated team. As deadlines approach, the very process meant to elevate code quality can become a barrier to success, creating a culture where developers feel undervalued and hesitant to share their insights.
The good news? You can transform your code review process into a constructive and engaging experience. By implementing strategic changes, you can cultivate a culture of open communication, collaborative learning, and continuous improvement.
This blog aims to provide developers and engineering managers with a comprehensive framework for optimizing the code review process, incorporating insights on leveraging tools like Typo and discussing the technical nuances that underpin effective code reviews.
Code reviews are a critical aspect of the software development lifecycle. They provide an opportunity to scrutinize code, catch errors early, and ensure adherence to coding standards. Here’s why code reviews are indispensable:
The primary function of code reviews is to identify issues before they escalate into costly bugs or security vulnerabilities. By implementing rigorous review protocols, teams can detect errors at an early stage, reducing technical debt and enhancing code stability.
Utilizing static code analysis tools like SonarQube and ESLint can automate the detection of common issues, allowing developers to focus on more intricate code quality aspects.
Code reviews foster an environment of shared learning and expertise. When developers engage in peer reviews, they expose themselves to different coding styles, techniques, and frameworks. This collaborative process enhances individual skill sets and strengthens the team’s collective knowledge base.
To facilitate this knowledge transfer, teams should maintain documentation of coding standards and review insights, which can serve as a reference for future projects.
Adherence to coding standards and best practices is crucial for maintaining a high-quality codebase. Effective code reviews enforce guidelines related to design patterns, performance optimization, and security practices.
By prioritizing clean, maintainable code, teams can reduce the likelihood of introducing technical debt. Establishing clear documentation for coding standards and conducting periodic training sessions can reinforce these practices.
The code review process inherently encourages open dialogue and constructive feedback. It creates a culture where developers feel comfortable discussing their approaches, leading to richer collaboration. Implementing pair programming alongside code reviews can provide real-time feedback and enhance team cohesion.
For new team members, code reviews are an invaluable resource for understanding the team’s coding conventions and practices. Engaging in the review process allows them to learn from experienced colleagues while providing opportunities for immediate feedback.
Pairing new hires with seasoned developers during the review process accelerates their integration into the team.
Despite their advantages, code reviews can present challenges that hinder productivity. It’s crucial to identify and address these issues to optimize the process effectively:
Extended review cycles can impede development timelines and lead to frustration among developers. This issue often arises from an overload of reviewers or complex pull requests. To combat this, implement guidelines that limit the size of pull requests, making them more manageable and allowing for quicker reviews. Additionally, establishing defined review timelines can help maintain momentum.
A lack of standardization in feedback can create confusion and frustration among team members. Inconsistency often stems from varying reviewer expectations. Implementing a standardized checklist or rubric for code reviews can ensure uniformity in feedback and clarify expectations for all team members.
If code reviews are concentrated among a few individuals, it can lead to bottlenecks that slow down the entire process. Distributing review responsibilities evenly among team members is essential to ensure timely feedback. Utilizing tools like GitHub and GitLab can facilitate the assignment of reviewers and track progress in real-time.
Sparse or overly critical feedback can hinder the collaborative nature of code reviews. Encouraging a culture of constructive criticism is vital. Train reviewers to provide specific, actionable feedback that emphasizes improvement rather than criticism.
Regularly scheduled code review sessions can enhance collaboration and ensure engagement from all team members.
To optimize your code review process effectively, leveraging the right tools is paramount. Typo offers a suite of features designed to enhance productivity and code quality:
Automating code analysis through Typo significantly streamlines the review process. Built-in linting and static analysis tools flag potential issues before the review begins, enabling developers to concentrate on complex aspects of the code. Integrating Typo with CI/CD pipelines ensures that only code that meets quality standards enters the review process.
Typo features an intuitive commenting system that allows reviewers to leave clear, actionable feedback directly within the code. This approach ensures developers receive specific suggestions, leading to more effective revisions. Implementing a tagging system for comments can categorize feedback and prioritize issues efficiently.
Typo provides detailed metrics and insights into code review performance. Engineering managers can analyze trends, such as recurring bottlenecks or areas for improvement, allowing for data-driven decision-making. Tracking metrics like review time, comment density, and acceptance rates can reveal deeper insights into team performance and highlight areas needing further training or resources.
Also read: Best Code Review Tools
In addition to leveraging tools like Typo, adopting best practices can further enhance your code review process:
Define clear objectives for code reviews, detailing what reviewers should focus on during evaluations. Developing a comprehensive checklist that includes adherence to coding conventions, performance considerations, and testing coverage ensures consistency and clarity in expectations.
Employ automation tools to reduce manual effort and improve review quality. Automating code analysis helps identify common mistakes early, freeing reviewers to address more complex issues. Integrating automated testing frameworks validates code functionality before reaching the review stage.
Fostering a culture of constructive feedback is crucial for effective code reviews. Encourage reviewers to provide specific, actionable comments emphasizing improvement. Implementing a “no blame” policy during reviews promotes an environment where developers feel safe to make mistakes and learn from them.
Finding the right balance between thorough reviews and maintaining development velocity is essential. Establish reasonable time limits for reviews to prevent bottlenecks while ensuring reviewers dedicate adequate time to assess code quality thoroughly. Timeboxing reviews can help maintain focus and reduce reviewer fatigue.
Regularly rotating reviewers prevents burnout and ensures diverse perspectives in the review process. Sharing responsibilities promotes knowledge transfer across the team and mitigates the risk of bottlenecks. Implementing a rotation schedule that pairs developers with different reviewers fosters collaboration and learning.
Also read: AI C͏o͏de Rev͏iews ͏for Remote͏ Teams
While developers execute the code review process, engineering managers have a critical role in optimizing and supporting it. Here’s how they can contribute effectively:
Engineering managers must actively facilitate communication within the team, ensuring alignment on the goals and expectations of code reviews. Regular check-ins can help identify roadblocks and provide opportunities for team members to express concerns or seek guidance.
Establishing a culture of accountability around code reviews is essential. Engineering managers should communicate clear expectations for both developers and reviewers, creating a shared understanding of responsibilities. Providing ongoing training on effective review practices reinforces these expectations.
Utilizing the metrics and insights provided by Typo enables engineering managers to monitor team performance during code reviews. Analyzing this data allows managers to identify trends and make informed decisions about adjustments to the review process, ensuring continuous improvement.
Engineering managers should cultivate a growth mindset within the team, encouraging developers to view feedback as an opportunity for learning and improvement. Creating an environment where constructive criticism is welcomed fosters a culture of continuous development and innovation. Encouraging participation in code review workshops or technical training sessions can reinforce this mindset.
An optimized code review process is not merely a procedural necessity; it is a cornerstone of developer productivity and code quality. By establishing clear guidelines, promoting collaboration, and leveraging tools like Typo, you can streamline the review process and foster a culture of continuous improvement within your team.
Typo serves as a robust platform that enhances the efficiency and effectiveness of code reviews, allowing teams to deliver higher-quality software at an accelerated pace. By embracing best practices and adopting a collaborative mindset, you can transform your code review process into a powerful driver of success.
In an ever-changing tech landscape, organizations need to stay agile and deliver high-quality software rapidly. DevOps plays a crucial role in achieving these goals by bridging the gap between development and operations teams.
In this blog, we will delve into how to build a DevOps culture within your organization and explore the fundamental practices and strategies that can lead to more efficient, reliable, and customer-focused software development.
DevOps is a software development methodology that integrates development (Dev) and IT operations (Ops) to enhance software delivery’s speed, efficiency, and quality. The primary goal is to break down traditional silos between development and operations teams and foster a culture of collaboration and communication throughout the software development lifecycle. This creates a more efficient and agile workflow that allows organizations to respond quickly to changes and deliver value to customers faster.
DevOps culture refers to a collaborative and integrated approach between development and operations teams. It focuses on breaking down silos, fostering a shared sense of responsibility, and improving processes through automation and continuous feedback.
The CALMS framework is used to understand and implement DevOps principles effectively. It breaks down DevOps into five key components:
The culture pillar focuses on fostering a collaborative environment where shared responsibility and open communication are prioritized. It is crucial to break down silos between development and operations teams and allow them to work together more effectively.
Automation emphasizes minimizing manual intervention in processes. This includes automating testing, deployment, and infrastructure management to enhance efficiency and reliability.
The lean aspect aims to optimize workflows, manage work-in-progress (WIP), and eliminate non-value-adding activities. This is to streamline processes to accelerate software delivery and improve overall quality.
Measurement involves collecting data to assess the effectiveness of software delivery processes and practices. It enables teams to make informed, fact-based decisions, identify areas for improvement, and track progress.
The sharing component promotes open communication and knowledge transfer among teams It facilitates cross-team collaboration, fosters a learning environment, and ensures that successful practices and insights are shared and adopted widely.
Don’t overwhelm teams completely with the DevOps haul. Begin small and implement DevOps practice gradually. You can start first with the team that is better aligned with DevOps principles and then move ahead with other teams in the organization. Build momentum with early wins and evolve practices as you gain experience.
Communication is a key. When done correctly, it promotes collaboration and a smooth flow of information across the organization. This further aligns organization operations and lets the engineering leaders make informed decisions.
Moreover, the combined working environment between the development and operations teams promotes a culture of shared responsibility and common objectives. They can openly communicate ideas and challenges, allowing them to have a mutual conversation about resources, schedules, required features, and execution of projects.
Apart from encouraging communication and a collaborative environment, create a clear plan that outlines where you want to go and how you will get there. Ensure that these goals are realistic and achievable. This will allow teams to see the bigger picture and understand the desired outcome, motivating them to move in the right direction.
Tools such as Slack, Kubernetes, Docker, and Jfrog help build automation capabilities for DevOps teams. These tools are useful as they automate repetitive and mundane tasks and allow teams to focus on value-adding work. This allows them to fail fast, build fast, and deliver quickly which enhances their efficiency and process acceleration, positively impacting DevOps culture. Ensure that instead of assuming, ask your team directly what part can be automated and further support facilities to automate it.
The organization must fully understand and implement CI/CD to establish a DevOps culture and streamline the software delivery process. This allows for automating deployment from development to production and releasing the software more frequently with better quality and reduced risks. The CI/CD tools further allow teams to catch bugs early in the development cycle, reduce manual work, and minimize downtime between releases.
Continuous improvement is a key principle of DevOps culture. Engineering leaders must look for ways to encourage continuous learning and improvement such as by training and providing upskilling opportunities. Besides this, give them the freedom to experiment with new tools and techniques. Create a culture where they feel comfortable making mistakes and learning from them.
The teams must ensure that delivering products quickly doesn’t mean compromising security. In DevOps culture, the organization must adopt a ‘Security-first approach’ by integrating security practices into the DevOps pipeline. To maintain a strong security posture, regular security audits and compliance checks are essential. Security scans should be conducted at every stage of the development lifecycle to continuously monitor and assess security.
Regularly monitor and track system performance to detect issues early and ensure smooth operation. Use metrics and data to guide decisions, optimize processes, and continuously improve DevOps practices. Implement comprehensive dashboards and alerts to ensure teams can quickly respond to performance issues and maintain optimal health.
In DevOps culture, the organization must emphasize the ever-evolving needs of the customers. Encourage teams to think from the customer’s perspective and keep their needs and satisfaction at the forefront of the software delivery processes. Regularly incorporate customer feedback into the development cycle to ensure the product aligns with user expectations.
Typo is an effective software engineering intelligence platform that offers SDLC visibility, developer insights, and workflow automation to build better programs faster. It can seamlessly integrate into tech tool stacks such as GIT versioning, issue tracker, and CI/CD tools.
It also offers comprehensive insights into the deployment process through DORA and other key metrics such as change failure rate, time to build, and deployment frequency. Moreover, its automated code tool helps identify issues in the code and auto-fixes them before you merge to master.
Typo has an effective sprint analysis feature that tracks and analyzes the team’s progress throughout a sprint. Besides this, It also provides 360 views of the developer experience i.e. captures qualitative insights and provides an in-depth view of the real issues.
Building a DevOps culture is essential for organizations to improve their software delivery capabilities and maintain a competitive edge. Implementing key practices as mentioned above will pave the way for a successful DevOps transformation.
DORA metrics are a compass for engineering teams striving to optimise their development and operations processes.
Consistently tracking these metrics can lead to significant and lasting improvements in your software delivery processes and overall business performance.
Below is a detailed guide on how Typo uses DORA to improve DevOps performance and boost efficiency:
In 2015, The DORA (DevOps Research and Assessment) team was founded by Gene Kim, Jez Humble and Nicole Forsgren to evaluate and improve software development practices. The aim was to improve the understanding of how organisations can deliver software faster, more reliable and of higher quality.
They developed DORA metrics that provide insights into the performance of DevOps practices and help organisations improve their software development and delivery processes. These metrics help in finding answers to these two questions:
DORA metrics helps in assessing software delivery performance based on four key (or accelerate) metrics:
Deployment Frequency measures the number of times that code is deployed into production. It helps in understanding team’s throughput and quantifying how much value is delivered to customers.
When organizations achieve a high Deployment Frequency, they can enjoy rapid releases without compromising the software’s robustness. This can be a powerful driver of agility and efficiency, making it an essential component for software development teams.
One deployment per week is standard. However, it also depends on the type of product.
Lead Time for Changes measures the time it takes for code changes to move from inception to deployment. The measurement of this metric offers valuable insights into the effectiveness of development processes, deployment pipelines, and release strategies.
By analysing the Lead Time for Changes, development teams can identify bottlenecks in the delivery pipeline and streamline their workflows to improve software delivery’s overall speed and efficiency. Shorter lead time states that the DevOps team is more efficient in deploying code.
Change Failure Rate gauges the percentage of changes that require hot fixes or other remediation after production. It reflects the stability and reliability of the entire software development and deployment lifecycle.
By tracking CFR, teams can identify bottlenecks, flaws, or vulnerabilities in their processes, tools, or infrastructure that can negatively impact the quality, speed, and cost of software delivery.
0% — 15% CFR is considered to be a good indicator of your code quality.
Mean Time to Recovery measures how quickly a team can bounce back from incidents or failures. It concentrates on determining the efficiency and effectiveness of an organisation’s incident response and resolution procedures.
A lower mean time to recovery is synonymous with a resilient system capable of handling challenges effectively.
The response time should be as short as possible. 24 hours is considered to be a good rule of thumb.
Reliability is a fifth metric that was added by the DORA team in 2021. It measures modern operational practices and doesn’t have standard quantifiable targets for performance levels.
Reliability comprises several metrics used to assess operational performance that includes availability, latency, performance and scalability that measures user-facing behaviour, software SLAs, performance targets, and error budgets.
Typo is an effective software engineering intelligence platform that offers SDLC visibility, developer insights, and workflow automation to build better programs faster. It offers comprehensive insights into the deployment process through key DORA metrics such as change failure rate, time to build, and deployment frequency.
Below is a detailed view of how Typo uses DORA to boost dev efficiency and team performance:
Typo’s DORA metrics dashboard has a user-friendly interface and robust features tailored for DevOps excellence. This helps in identifying bottlenecks, improves collaboration between teams, optimises delivery speed and effectively communicates team’s success.
DORA metrics dashboard pulls in data from all the sources and presents in a visualised and detailed way to engineering leaders and development team.
DORA metrics helps in many ways:
Firstly, define clear and measurable objectives. Consider KPIs that align with your organisational goals. Whether it’s improving deployment speed, reducing failure rates, or enhancing overall efficiency, having a well-defined set of objectives will help guide your implementation of the dashboard.
Gain a deeper understanding of DORA metrics by exploring the nuances of Deployment Frequency, Lead Time, Change Failure Rate, and MTTR. Then, connect each of these metrics with your organisation’s DevOps goals to have a comprehensive understanding of how they contribute towards improving overall performance and efficiency.
Follow specific guidelines to properly configure your dashboard. Customise the widgets to accurately represent important metrics and personalise the layout to create a clear and intuitive visualisation of your data. This ensures that your team can easily interpret the insights provided by the dashboard and take appropriate actions.
To ensure the accuracy and reliability of your DORA Metrics, establish strong data collection mechanisms. Configure your dashboard to collect real-time data from relevant sources, so that the metrics reflect the current state of your DevOps processes.
Integrate automation tools to optimise the performance of your DORA Metrics Dashboard.
By utilising automation for data collection, analysis, and reporting processes, you can streamline routine tasks. This will free up your team’s time and allow them to focus on making strategic decisions and improvements.
To get the most out of your well-configured DORA Metrics Dashboard, use the insights gained to identify bottlenecks, streamline processes, and improve overall DevOps efficiency. Analyse the dashboard data regularly to drive continuous improvement initiatives and make informed decisions that will positively impact your software development lifecycle.
Typo’s dashboard provides clear and intuitive visualisations of the four key DORA metrics:
It tracks how often new code is deployed to production, highlighting the team’s productivity.
By integrating with your CI/CD tool, Typo calculates Deployment Frequency by counting the number of unique production deployments within the selected time range. The workflows and repositories that align with production can be configured by you.
It measures the time it takes from code being committed to it being deployed in production, indicating the efficiency of the development pipeline.
In the context of Typo it is the average time all pull requests have spent in the “Coding”, “Pickup”, “Review” and “Merge” stages of the pipeline. Typo considers all the merged Pull Requests for the main/master/production branch for the selected time range and calculates the average time spent by each Pull Request in every stage of the pipeline. No open/draft Pull Requests are considered in this calculation.
It shows the percentage of deployments causing a failure in production, reflecting the quality and stability of releases.
There are multiple ways this metric can be configured:
To calculate the final percentage, the total number of failures are divided by the total number of deployments (this can be picked either from the Deployment PRs or from the CI/CD tool deployments).
It measures the time taken to recover from a failure, showing the team’s ability to respond to and fix issues.
The way a team tracks production failure (CFR) defines how MTTR is calculated for that team. If a team considers a production failure as :
DORA metrics deliver crucial insights into team performance. Monitoring Change Failure Rate and Mean Time to Recovery helps leaders ensure their teams are building resilient services with minimal downtime. Similarly, keeping an eye on Deployment Frequency and Lead Time for Changes assures engineering leaders that the team is maintaining a swift pace.
Together, these metrics offer a clear picture of how well the team balances speed and quality in their workflows.
One of the ways organizations are implementing is through a continuous feedback process. While it may seem a straightforward process, it is not. Every developer takes feedback in different ways. Hence, it is important to engineer the feedback the right way.
Below are a few ways why continuous feedback is beneficial for both developers and engineering leaders:
Keeps everyone on the same page: Feedback enables individuals to be on the same page. No matter what type of tasks they are working on. It allows them to understand their strengths and improve their blind spots. Hence, provide high-quality work.
Facilitates improvement: Feedback enables developers the areas they need to improve and the opportunities they can grab according to their strengths. With the right context and motivation, it can encourage software developers to work on their personal and professional growth.
Nurtures healthy relationships: Feedback fosters open and honest communication. It lets developers be comfortable in sharing ideas and seeking support without any judgements even when they aren’t performing well.
Enhances user satisfaction: Feedback helps developers to enhance their quality of work. This can have a direct impact on user satisfaction which further positively affects the organization.
Strength performance management: Feedback enables you to set clear expectations, track progress, and provide ongoing support and guidance to developers. This further strengthens their performance and streamlines their workflow.
There are a lot of things to consider when giving effective and honest feedback. We’ve divided the process into three sections. Do check it out below:
Plan in advance how will you start the conversation, what is worth mentioning, and what is not. For example, if it is related to pull requests, can start by discussing their past performance related to the same. Further, you can talk about how well are they performing, whether they are delivering the work on time, rating their performance and action plan, and if there are any challenges they are facing. Make sure to relate it to the bigger picture.
When framed appropriately and constructively, it helps in focusing on improvement rather than criticism. It also enables developers to take feedback the right way and help them grow and succeed.
Observe and note down everything related to the developers. Track their performance continuously. Jot down whatever noticed even if it is not worth mentioning during the feedback session. It allows you to share feedback more accurately and comprehensively. It also helps you to identify the trends and patterns in developer performance and lets them know that the feedback isn’t based on isolated incidents but rather the consistent observation.
For example, XYZ is a software developer at ABC organization. The engineering leader observed XYZ for three months before delivering effective feedback. She told him:
So, the engineering leader was able to discuss effectively his strengths and areas of improvement.
Before offering feedback to software development teams, make sure you are well aware of the differences between constructive feedback and criticism. Constructive feedback encourages developers to enhance their personal and professional development. On the other hand, criticism enables developers to be defensive and hinder their progress.
Constructive feedback allows you to focus on the behavior and outcome of the developers and help them by providing actionable insights while criticism focuses on faults and mistakes without providing the right guidance.
For example,
Situation: A developer’s recent code review missed several critical issues.
Feedback: “Your recent code review missed a few critical issues, like the memory leak in the data processing module. Next time, please double-check for potential memory leaks. If you’re unsure how to spot them, let’s review some strategies together.”
Criticism: “Your code reviews are sloppy and miss too many important issues. You need to do a better job.”
Review previous feedback given to developers before the session. Check what was last discussed and make sure to bring it up again. Also, include those that were you tracking during this time and connect them with the previous feedback process. Look for metrics such as pull request activity, work progress, team velocity, work log, check-ins, and more to get in-depth insights about their work. You can also gather peer reviews to get 360-degree feedback and understand better how well individuals are performing.
This makes your feedback balanced and takes into account all aspects of developers’ contributions and challenges.
The feedback shouldn’t be a top-down approach. It must go both ways. You can start by bringing up the discussion that happened in the previous feedback session. Know their opinion and perspective on certain topics and ideas. Make sure that you ask questions to make them realize that you respect their opinions and want to hear what they want to discuss.
Now, share your feedback based on the last discussion, observations, and performance. You can also modify your feedback based on their perspective and reflections. It allows the feedback to be detailed and comprehensive.
When you have shared their areas of improvement, make sure you provide them with clear actionable plans as well. Discuss with them what needs immediate attention and what steps can they take. Set small goals with them as it makes it easier to focus on them and let them know that their goals are important. You must also schedule follow-up meetings with them after they reach every step and understand if they are facing any challenges. You can also provide resources and tools that can help them attain their goals.
Developed by the Center for Creative Leadership, the SBI stands for situation, behavior, and impact framework. It includes:
Example: Last week’s team collaboration on the new feature development.
Example: “You did not participate actively in the brainstorming sessions and missed a few important meetings.”
Example: “This led to a lack of input from your side, and we missed out on potentially valuable ideas. It also caused some delays as we had to reschedule discussions.”
Final words could be: “Please ensure to attend all relevant meetings and actively participate in discussions. Your contributions are important to the team.”
This allows for delivering feedback that is clear, actionable, and respectful. It makes it relevant and directly tied to the situation. Note that, this framework is for both positive and negative feedback.
It is also important to know if any constraints are negatively impacting their performance. It could include tight deadlines or a heavy workload that is hampering their productivity or facing health issues due to which they aren’t able to focus properly. Ask them while you deliver feedback to them. You can further create actionable plans accordingly. This shows developers that you care for them and makes the feedback more personalized and relevant. Besides this, it also allows you to share tangible improvements rather than adding more pressure.
For example: “During the last sprint, there were a few missed deadlines. Is there something outside of work that might be affecting your ability to meet these deadlines? Please let me know if there’s anything we can do to accommodate your situation.”
Before concluding the meeting, ask them if there’s anything they would like to discuss. It could likely be that they have missed out on something or it wasn’t bought up during the session.
Afterwards, summarize what has been discussed. Ask the developers what are their key takeaways from the session and share your perspective as well. You can document the summary to help you and developers in the future feedback meetings. This gives mutual understanding and ensures that both are on the same page.
Keep a record of what was discussed during this session and action plans provided to the developers. You can take a look at them in future feedback meetings or performance evaluations. An example of the structure of summary:
Ensure you give them measurable goals and timelines during the feedback session. Monitor their progress through check-ins, provide ongoing support and guidance, and keep discussing the challenges or roadblocks they are facing. It helps the developers stay on track and feel supported throughout their journey.
Typo is an effective software engineering intelligence platform that can help in improving the feedback process within development teams. Here’s how Typo’s features can be leveraged to enhance feedback sessions:
For more information, visit our website!
Software developers deserve high-quality feedback. It not only helps them identify their blind spots but also polishes their skills. The feedback loop lets developers know where they stand and the recognition they deserve.
Building a high-performing engineering team is crucial for the success of any company, especially in the dynamic and constantly evolving world of technology. Whether you’re a startup on the rise or an established enterprise looking to maintain your competitive edge, having a well-structured engineering team is essential.
This blog will explore the intricacies of building and structuring engineering teams for scale and success. We’ll cover many topics, including talent acquisition, skill development, team management, and more.
Whether you’re a CTO, a team leader, or an entrepreneur looking to build your own engineering team, this blog will equip you with the knowledge and tools to create a high-performing engineering team that can drive innovation and help you achieve your business goals.
Before we dive into the specifics of team structure, it’s vital to understand the dynamics that shape engineering teams. Various factors, including team size, communication channels, leadership style, and cultural fit, influence these dynamics. Each factor plays a significant role in determining how well a team operates.
The size of a team can significantly impact its operation. Smaller teams tend to be more agile and flexible, making it easier for them to make quick decisions and respond to project changes. On the other hand, larger teams can provide more resources, skills, and knowledge, but they may struggle with communication and coordination.
Effective communication is essential for any team’s success. In engineering teams, communication channels play a significant role in ensuring team members can collaborate effectively. Different communication channels, such as email, chat, video conferencing, or face-to-face, can impact the team’s effectiveness.
A team leader’s leadership style can significantly impact the team’s effectiveness. Autocratic leaders tend to make decisions without input from team members, while democratic leaders encourage team members to participate in decision-making. Moreover, transformational leaders inspire and motivate team members to achieve their best.
Cultural fit refers to how well team members align with the team’s values, norms, and beliefs. A team that has members with similar values and beliefs is more likely to work well together and be more productive. In contrast, a team with members with conflicting values and beliefs may struggle to work effectively.
Scaling engineering teams can present challenges, and planning and strategizing thoughtfully is crucial to ensure that the team remains effective. Understanding the dynamics that shape engineering teams can help teams overcome these challenges and work together effectively.
An engineering team must be diverse and collaborative. Each team member should specialize in a particular area but also be able to comprehend and collaborate with others in building a product.
A few of them include:
The software development team lead plays a crucial role in guiding and coordinating the efforts of the software development team. They could have under 10 to hundreds of team members under their lead.
Software developers write the code, their job is purely technical and they build the product. Most of them are individual contributors i.e. they have no management or HR responsibilities.
Product managers define the product vision, gather and prioritize requirements, and deal with collaboration with engineering teams.
Designers create user-friendly interfaces, develop prototypes to visualize concepts and iterate on feedback-based designs.
Once the dynamics of engineering teams are understood, organizations can apply key principles to build and structure teams for scale. From defining goals and establishing role clarity to fostering a culture of collaboration and innovation, these principles serve as a foundation for effective team building.
There is no one-size-fits-all approach to structuring engineering teams. Different structures may be more suitable depending on the organization’s size, industry, and goals. Organizations can identify the structure that best aligns with their unique needs and objectives by exploring various approaches.
The top two approaches are:
When teams are formed based on the project for a defined period. It is a traditional way where engineers and designers are selected from their respective departments and tasked with project-related work.
It may seem logical, but it poses challenges. Project-based teams can prioritize short-term objectives and collaborating with unfamiliar team members can lead to communication gaps, particularly between developers and other project stakeholders.
When teams are aligned around specific products or features to promote ownership and accountability. Since this team structure is centered around the product, it is a long-term project, and team members are bound to work together more efficiently.
As the product gains traction and attracts users, the team needs to adapt to a changing environment i.e. restructuring and hiring specialists.
Other approaches include:
In engineering organizations, there is a tendency to rely heavily on one person for all responsibilities rather than distributing them among team members. It not only leads to bottlenecks and inefficiencies but also, slows down progress and the inability to deliver quality products.
The two most common communication issues while structuring and building engineering teams are – Alignment and context-switching between engineering teams. This increases the miscommunication among team members and leads to duplication of work, neglected responsibilities, and coverage gaps.
When engineering leaders micromanage developers, it can hinder productivity, innovation, and overall team effectiveness. Hence, having a structure that fosters optimization, ownership, and effectiveness is important for building an effective team.
Scaling an engineering team requires careful planning and execution. Here are the best practices to build a team that scales well:
Building and structuring engineering teams for scale is a multifaceted endeavor that requires careful planning, execution, and adaptation.
But this doesn’t end here! Measuring a team’s performance is equally important to build an effective team. This is where Typo comes in!
It is an intelligent engineering management platform used for gaining visibility, removing blockers, and maximizing developer effectiveness. It gives a comparative view of each team’s performance across velocity, quality, and throughput.
For more information, check out our website!
Agile project management relies on iterative development cycles to deliver value efficiently. Central to this methodology is the iteration burndown chart, a visual representation of work progress over time. In this blog, we’ll explore leveraging and enhancing the iteration burndown chart to optimize Agile project outcomes and team collaboration.
An iteration burndown chart is a graphical representation of the total work remaining over time in an Agile iteration, helping teams visualize progress toward completing their planned work.
It typically includes an ideal line representing the planned progress, an actual line indicating the real progress, and axes to represent time and work remaining.
The chart enables teams to monitor their velocity, identify potential bottlenecks, and make data-driven decisions to ensure successful iteration completion.
Understanding the advantages of iteration burndown charts is key to appreciating their value in Agile project management. From enhanced visibility to improved decision-making, these charts offer numerous benefits that can positively impact project outcomes.
Crafting an effective iteration burndown chart requires a thorough and step-by-step approach. Here are some detailed guidelines to help you create a well-designed burndown chart that accurately reflects progress and facilitates efficient project management:
By following these detailed guidelines, you’ll be able to create an accurate and effective iteration burndown chart that can help you and your team monitor your project’s progress and manage it more efficiently.
While creating a burndown chart is a crucial first step, maximizing its effectiveness requires ongoing attention and refinement. These tips will help you harness the full potential of your iteration burndown chart, empowering your development teams to achieve greater success in Agile projects.
Continuous improvement lies at the heart of Agile methodology, and your iteration burndown chart is no exception. By incorporating feedback, analyzing historical data, and experimenting with different approaches, you can refine your chart to better meet your team’s and stakeholders’ needs.
A burndown chart is great for evaluating the ratio of work remaining and the time it takes to complete the work. However, relying solely on a burndown chart is not the right way due to certain limitations.
Although creating a burndown chart in Excel is easy, entering data manually requires more time and effort. This makes the work repetitive and tiresome after a certain point.
The Burndown chart helps to track the progress of completing tasks or user stories over time within a sprint or iteration. But, it doesn’t provide insights about the specific types of issues or tasks being worked on. It includes shipping new features, determining technical debt, and so on.
A burndown chart doesn’t differentiate between an easy and difficult task. It considers all of them equal, regardless of their size, complexity, or effort required to complete it. Hence, leading to ineffective outlines of project progress. This further potentially masks critical issues and hinders project management efforts.
The burndown chart primarily focuses on tracking remaining work throughout a sprint, but it doesn’t directly indicate the predictability of completing that work within the sprint timeframe. It lacks insight into factors like team velocity fluctuations or scope changes, which are crucial for assessing sprint predictability accurately.
Typo’s sprint analysis is an essential tool for any team using an agile development methodology. It allows agile teams to track and analyze overall progress throughout a sprint timeline. It helps to gain visual insights into how much work has been completed, how much work is still in progress, and how much time is left in the sprint. This information can help to identify any potential problems early on and take corrective action.
Our sprint analysis feature uses data from Git and issue management tools to provide insights into how software development teams are working. They can see how long tasks are taking, how often they’re being blocked, and where bottlenecks are occurring.
It is easy to use and can be integrated with existing Git and Jira/Linear/Clickup workflows.
The iteration burndown chart is a vital tool in Agile project management. It offers agile and scrum teams a clear, concise way to track progress and make data-driven decisions.
However, one shouldn’t rely solely on the burndown charts. Moreover, there are various advanced sprint analysis tools such as Typo in the market that allow teams to track and gain visual insights into the overall progress of the work.
Jira is a widely used project management tool that enables teams to work together efficiently and achieve outstanding outcomes. The Jira dashboard is a vital component of this tool, offering teams valuable insights, metrics, and project visibility. In this journey, we will explore the potential of Jira dashboards and learn how to leverage their full capabilities.
A Jira dashboard serves as the nerve center of project activity, offering a consolidated view of tasks, progress, and key metrics. It gives stakeholders a centralized location to monitor project health, track progress, and make informed decisions.
These modular components provide specific information and functionality, such as task lists, burndown charts, and activity streams. There are several gadgets built into project management tools, such as filter results gadget, issue statistics gadget, and road map gadget. However, additional gadgets can also be downloaded from third-party marketplaces. Some of them are the pivot gadget and gauge gadget.
To build an effective project management dashboard, start with the essentials: overall progress, work split by person or sub-section, and high-risk issues front and center. This ensures that the most critical data is easily accessible and actionable. Here's a list of must-have gadgets to consider:
Once you've added these key components, you'll have a robust dashboard ready to streamline your project management workflow.
Jira dashboards host various reports, including velocity charts, sprint summaries, and issue statistics, offering valuable insights into team performance, and project trends.
Jira dashboards are used for several reasons:
The default dashboard is also known as the system dashboard. It is the screen Jira users see the first time they log in. It includes gadgets from Jira’s pre-installed selection and is limited to only one dashboard page.
Creating custom dashboards requires careful planning and consideration of project objectives and team requirements. Let’s explore the step-by-step process of crafting a bespoke dashboard:
Log in to your Jira account. Go to the dashboard and click ‘Create Dashboard’.
Start by defining the objectives and goals of your dashboard page. Determine what information is crucial for your team to track and monitor, and tailor your dashboard accordingly.
Choose gadgets and reports that align with your project’s needs and objectives. When curating your dashboard content, consider factors such as team workflow, project complexity, and stakeholder requirements.
Choose your preferred dashboard layout and configuration to ensure optimal visibility and usability for all stakeholders. Arrange gadgets and reports logically and intuitively to facilitate easy navigation and information access.
Embrace an iterative dashboard refinement approach. Solicit user and stakeholder feedback to improve its effectiveness and usability continuously. Regularly assess and update your dashboard to reflect evolving project needs and priorities.
Don’t forget to share the Jira dashboard with the team. This ensures transparency and fosters a collaborative culture. By granting appropriate permissions, they can view and interact with the dashboard and get real-time updates.
Imagine the power of walking into a status meeting and instantly knowing how projects are progressing without waiting for updates. Here's how you can create your own dashboard to monitor progress efficiently before any discussions start.
Begin by setting up a fresh dashboard on your project management software:
To ensure your dashboard gives you a clear picture of the project status, integrate these key components:
For visualization, you might include:
With your dashboard populated, you can start your day with a glance that informs your intuition about project statuses.
Ensure your roadmap focuses on a single project for simplicity. Configure it to display the essential metrics that align with your meeting's goals.
Final Touches and Review
By following these steps, you'll build a dashboard that empowers you to walk into meetings well-prepared and informed, streamlining discussions and decision-making.
A personal dashboard is tailored to individual needs and offers various advantages in streamlining workflow management and improving productivity. It provides a centralized platform for organizing and visualizing user’s tasks, different projects, issues, etc.
This dashboard gives real-time updates on whether the team is on pace to meet a sprint goal. It offers a glimpse of how much work is left in the queue and how long your team will take to complete it. Moreover, the sprint burndown dashboard allows you to jump on any issue when the remaining workload is pacing slower than the delivery date.
The workload dashboard, also known as the monitor resource dashboard tracks the amount of work assigned to each team member and adjusts their workload accordingly. It helps identify workload patterns and plan resource allocation.
To ensure that your target release dates are realistic, it's crucial to monitor the workload effectively and adjust your strategies accordingly. Here's how you can do that:
By following these steps, you can maintain visibility over your work progress and adjust timelines appropriately, ensuring that release targets remain feasible given the current workload.
The issue tracking dashboard allows users to quickly identify and prioritize the most important issues. It focuses on providing visibility into the status and progress of issues or tickets within a project.
In any project, some tasks inherently carry more risk due to their complexity or resource requirements. To effectively manage these, it's crucial to identify and keep track of them using project management tools. Here’s how you can streamline this process:
Start by scrutinizing tasks that demand extensive time commitments—these often signal complex challenges. A significant time estimate can indicate potential hurdles or even hidden intricacies.
A good strategy to isolate these high-risk items is by using advanced filter functions in your project management software. Here’s a step-by-step approach:
Once you've created your filter, leverage the dashboard tools within your project management software to keep these items visible:
By maintaining a clear focus on high-risk tasks through strategic filtering and dashboard visualization, you ensure that potential issues are addressed proactively, reducing the likelihood of them derailing your project.
To maximize the impact of your Jira dashboard, consider the following best practices:
Share your dashboard with relevant stakeholders to promote transparency and collaboration. Encourage team members to actively engage with the dashboard and provide feedback to drive continuous improvement.
Integrating your Jira dashboard with other tools and systems is the best way to automate data capture and reporting processes. Leverage integration capabilities to streamline workflow management and enhance productivity.
Empower project teams and leaders to make informed decisions by providing access to actionable insights and performance metrics through the dashboard. Encourage data-driven discussions and decision-making to drive project success.
Take your Jira dashboard customization to the next level with advanced techniques and strategies:
Implement filters and contextualization techniques to personalize the dashboard experience for individual users or specific project phases. Allow users to tailor the dashboard view based on their preferences and requirements.
To effectively monitor progress towards your next project milestone, it's crucial to create a tailored search filter. This filter allows you to focus on the most relevant data for your project. Here's a step-by-step guide to setting this up:
By setting up this filter, you can maintain a clear view of your project’s progress towards the next milestone, ensuring everyone on your team is aligned with the priorities.
Utilize dynamic updating capabilities to ensure that your dashboard reflects real-time changes and updates in project data. Implement automated refresh intervals and notifications to keep stakeholders informed and engaged.
Explore the possibilities of custom gadgets and extensions to extend the functionality of your Jira dashboard. Develop custom gadgets or integrate third-party extensions to address unique project requirements and enhance user experience.
By incorporating these strategies, you can ensure that your project management dashboard remains a powerful tool for driving project success and adapting to the evolving demands of your release cycle.
Typo’s sprint analysis feature can be seamlessly integrated with the Jira dashboard. It allows to track and analyze the team’s progress throughout a sprint and provides valuable insights into work progress, work breakup, team velocity, developer workload, and issue cycle time.
The benefits of Sprint analysis feature are:
A well-designed Jira dashboard is a catalyst for project excellence, providing teams with the insights and visibility they need to succeed. By understanding its components, crafting a tailored dashboard, and maximizing its impact, you can unlock Jira dashboards’ full potential and drive your projects toward success.
Furthermore, while Jira dashboards offer extensive functionalities, it’s essential to explore alternative tools that may simplify the process and enhance user experience. Typo is one such tool that streamlines project management by offering intuitive dashboard creation, seamless integration, and a user-friendly interface. With Typo, teams can effortlessly visualize project data, track progress, and collaborate effectively, ultimately leading to improved productivity and project outcomes. Explore Typo today and revolutionize your project management experience.
Scrum has become one of the most popular project management frameworks, but like any methodology, it’s not without its challenges. Scrum anti-patterns are common obstacles that teams may face, leading to decreased productivity, low morale, and project failure. Let’s explore the most prevalent Scrum anti patterns and provide practical solutions to overcome them.
A lack of a clear Definition of Done (DoD) can cause teams to struggle to deliver shippable increments at the end of each sprint. It can be due to a lack of communication and transparency. This ambiguity leads to rework and dissatisfaction among stakeholders.
Collaboration is key to establishing a robust DoD. Scrum team members should work together to define clear criteria for completing each user story. These criteria should encompass all necessary steps, from development to testing and acceptance. The DoD should be regularly reviewed and refined to adapt to evolving project needs and ensure stakeholder satisfaction.
One of the common anti patterns is overcommitment during sprint planning meetings. It sets unrealistic expectations, leading to compromised quality and missed deadlines.
Base sprint commitments on past performance and team capacity rather than wishful thinking. Focus on realistic sprint goal setting to ensure the team can deliver commitments consistently. Emphasize the importance of transparency and communication in setting and adjusting sprint goals.
Micromanagement stifles team autonomy and creativity, leading to disengagement, lack of trust and reduced productivity.
Scrum Masters should adopt a servant-leadership approach, empowering teams to self-organize and make decisions autonomously. They should foster a culture of trust and collaboration where team members feel comfortable taking ownership of their work. They should provide support and guidance when needed, but avoid dictating tasks or solutions.
Disengaged Product Owners fail to provide clear direction and effectively prioritize the product backlog, leading to confusion and inefficiency.
Encourage regular communication and collaboration between the Product Owner and the development team. Ensure that the Product Owner is actively involved in sprint planning, backlog refinement, and sprint reviews. Establish clear channels for feedback and decision-making to ensure alignment with project goals and stakeholder expectations.
Failing to embrace a mindset of continuous improvement and adaptation leads to stagnation and inefficiency.
Prioritize retrospectives and experimentation to identify areas for improvement. Encourage a culture of learning and innovation where team members feel empowered to suggest and implement changes. Emphasize the importance of feedback loops and iterative development to drive continuous improvement and adaptation.
Allowing the project scope to expand unchecked during the sprint leads to incomplete work and missed deadlines.
Define a clear product vision and prioritize features based on value and feasibility. Review and refine the product backlog regularly to ensure that it reflects the most valuable and achievable items. Encourage stakeholder collaboration and feedback to validate assumptions and manage expectations.
Siloed teams hinder communication and collaboration, leading to bottlenecks and inefficiencies.
Foster a collaboration and knowledge-sharing culture across teams and disciplines. Encourage cross-functional teams to work together towards common goals. Implement practices such as pair programming, code reviews, and knowledge-sharing sessions to facilitate collaboration and break down silos.
Rushing through sprint retrospective and review meetings results in missed opportunities for feedback and improvement.
Allocate sufficient time for thorough discussion and reflection during sprint review and retrospective meetings. Encourage open and honest communication and ensure that all development team members have a chance to share their insights and observations. Based on feedback and retrospective findings, prioritize action items for continuous improvement.
Product Owners making unrealistic commitments disrupt the team’s focus and cause delays.
Establish a clear process for managing changes to the product backlog. Encourage collaboration between the Product Owner and the development team to negotiate realistic commitments and minimize disruptions during the sprint. Prioritize backlog items based on value and effort to ensure the team consistently delivers on its commitments.
Limited involvement or feedback from stakeholders leads to misunderstandings and dissatisfaction with the final product.
Engage stakeholders early and often throughout the project lifecycle. Solicit feedback and involve stakeholders in key decision-making processes. Communicate project progress regularly and solicit input to ensure alignment with stakeholder expectations and requirements.
Neglecting to address technical debt results in decreased code quality, increased bugs, and slower development velocity over time.
Allocate time during each sprint for addressing technical debt alongside new feature development. Encourage collaboration between developers and stakeholders to prioritize and tackle technical debt incrementally. Invest in automated testing and refactoring to maintain code quality and reduce technical debt accumulation.
Failing to implement continuous integration and deployment practices leads to integration issues, longer release cycles, and reduced agility.
Establish automated CI/CD pipelines to ensure that code changes are integrated and deployed frequently and reliably. Invest in infrastructure and tools that support automated testing and deployment. Encourage a culture of automation and DevOps practices to streamline the development and delivery process.
Daily scrum meeting is usually used synonymously with daily status meetings. This loses its focus on collaboration and decision-making. Sometimes, team members don’t find any value in these meetings leading to disengagement and decreased motivation.
In daily scrums, the focus should only be on talking to each other about what’s the most important work to get done that day and how to do it. Encourage team members to collaborate to tackle problems and achieve sprint goals. Moreover, keep the daily scrums short and timeboxed, typically to 15 minutes.
Successfully implementing Scrum requires more than just following the framework—it demands a keen understanding of potential pitfalls and proactive strategies to overcome them. By addressing common Scrum anti patterns, teams can cultivate a culture of collaboration, efficiency, and continuous improvement, leading to better project outcomes and stakeholder satisfaction.
However, without the right tools, identifying and addressing these anti-patterns can be daunting. That’s where Typo comes in. Typo is an intuitive project management platform designed to streamline Agile processes, enhance team communication, and mitigate common Scrum challenges.
With Typo, teams can effortlessly manage their Scrum projects, identify and address anti-patterns in real-time, and achieve greater success in their Agile endeavors.
So why wait? Try Typo today and elevate your Scrum experience to new heights!
"Jira software has become the backbone of project management for many teams across various industries. Its flexibility and powerful features make it an invaluable tool for organizing tasks, tracking progress, and collaborating effectively. However, maximizing its potential requires more than just basic knowledge. To truly excel in Jira ticket management, you must implement strategies and best practices that streamline your workflows and enhance productivity.
Jira is a popular project management tool developed by Atlassian, commonly used for issue tracking, bug tracking, and project management. Jira ticket management refers to the process of creating, updating, assigning, prioritizing, and tracking issues within Jira.
A Jira ticket acts as a digital record of a task, issue, or request within your Jira system. Here are the key elements that a Jira ticket typically contains:
These components keep everything organized and explained, ensuring your team stays on the same page while managing projects efficiently. By understanding the detailed structure of a Jira ticket, teams can improve their workflow and collaboration.
Creating a ticket in Jira is a straightforward process that helps streamline your workflow and ensures tasks are tracked efficiently. Here's how you can do it:
By following these steps, your ticket will be successfully created and primed for oversight until resolution. This systematic approach ensures clarity and accountability across your team.
Creating a Jira Service Management project and selecting the appropriate request types is a straightforward process. Follow these steps to get started:
By following these steps, you’ll establish a structured project environment tailored to your team's service management needs while keeping the setup manageable and adaptable.
One of the major challenges with the Jira ticketing platform is that it requires a lot of tedious and manual work. This leads to developer frustration, incomplete ticket updates, and undocumented work.
To mitigate this, consider automating repetitive tasks where possible. Use Jira's automation tools to streamline processes, such as auto-assigning tickets or updating statuses, to reduce manual input and enhance team productivity.
Setting up Jira software to align with the specific needs of a team or project can be complicated. Configuring workflows, custom fields, and permissions requires careful planning and may involve a learning curve for administrators.
Simplify Workflows: While it's tempting to create intricate workflows to cover every scenario, simplicity is key. Focus on the essential steps and decision points to resolve tickets efficiently. Involve your team in mapping out workflows to ensure they are intuitive and effective for everyone involved.
Due to the above-mentioned points, it can lead to software development team work becoming untracked and invisible. Hence, the team lacks data hygiene which further leads top management to make decisions with incomplete information. This can further impact planning accuracy as well.
Set Clear Guidelines: Establishing clear, concise guidelines for ticket management can help maintain data integrity. Define what information should be included in ticket descriptions, how to categorize and prioritize tasks, and when to update or close tickets. Ensuring these guidelines are easily accessible and consistently followed will promote better data hygiene.
Customize for Better Fit: Avoid using Jira in its most basic form. Explore customization options to tailor the system to your team’s unique needs. Create custom fields and design workflows that align with your processes. Set up dashboards to display key metrics and integrate Jira with other tools your team uses to enhance visibility and efficiency.
By addressing these challenges with thoughtful solutions, you can transform Jira into a powerful tool that supports your team’s workflow and decision-making processes effectively.
Below are some essential tips to help you manage your Jira tickets better:
Developers often find it labor-intensive to keep tickets updated. Hence, JIRA provides some automation that eases the work of developers. Although these automations are a bit complex initially, once mastered, they offer significant efficiency gains. Moreover, they can be customized as well.
Here are a few JIRA automation that you can take note of:
This is one of the most commonly used automation that involves ensuring accountability for an issue by automatically assigning it to its creator. It ensures that there is always a designated individual responsible for addressing the matter, streamlining workflow management and accountability within the team.
This automation can be customized to suit various scenarios, such as applying it to epics and stories or refining it with specific conditions tailored to your workflow. For example, when a bug issue is reported, you can set up automation to automatically create tasks aimed at resolving the problem. It not only streamlines the process but also ensures that necessary tasks are promptly initiated, enhancing overall efficiency in issue management.
Implementing this advanced automation involves creating a duplicate of an issue in a different project when it undergoes a specific transition. It also leaves a comment on the original issue to establish a connection between them. It becomes particularly valuable in scenarios where one project is dedicated to managing customer requests, while another project is focused on executing the actual work.
This automation automatically computes and assigns a due date to an issue when it’s moved from the backlog to the ‘In Progress’ status. This streamlines the process of managing task timelines, ensuring that deadlines are promptly established as tasks transition into active development stages.
If you're looking to make your Service Level Agreements (SLAs) visible to external stakeholders within Jira Service Management, follow these steps to ensure seamless transparency:
Utilizing these configuration options within Jira allows for greater transparency at every stage of your service process. This ensures that all stakeholders have the necessary insights into SLA metrics, thereby enhancing accountability and improving service delivery.
Remember, integrating these settings effectively helps leverage the full potential of Jira Service Management, turning your ticketing system into a powerful tool for stakeholder engagement.
Establishing clear guidelines for creating tickets ensures consistency across your projects. Include essential details such as a descriptive title, priority level, assignee, and due date. This ensures that everyone understands what needs to be done at a glance, reducing confusion and streamlining the workflow.
Moreover, standardizing ticket creation practices fosters alignment within your team and improves communication. When everyone follows the same format for ticket creation, it becomes easier to track progress, assign tasks, and prioritize work effectively. Consistency also enhances transparency, as stakeholders can quickly grasp the status of each ticket without needing to decipher varying formats.
Tailoring Jira workflows to match your team’s specific processes and requirements is essential for efficient ticket management. Whether you follow Agile, Scrum, Kanban, or a hybrid methodology, configure workflows that accurately reflect your workflow stages and transitions. This customization ensures your team can work seamlessly within Jira, optimizing productivity and collaboration.
Customizing workflows allows you to streamline your team’s unique processes and adapt to changing project needs. For example, you can define distinct stages for task assignment, development, testing, and deployment that reflect your team’s workflow. Custom workflows empower teams to work more efficiently by clarifying task progression and facilitating smoother handoffs between team members.
Not all tasks are created equal in Jira. Use priority fields to categorize tickets based on urgency and importance. This strategic prioritization helps your team focus on high-priority items and prevents critical tasks from slipping through the cracks. By prioritizing effectively, you can ensure that important deadlines are met and resources are allocated efficiently.
Effective prioritization involves considering various factors, such as project deadlines, stakeholder requirements, and resource availability. By assessing the impact and urgency of each task, teams can more effectively allocate their time and resources. Regularly reviewing and updating priorities ensures your team remains agile and responsive to changing project needs.
Leverage tags or custom fields to add context to your tickets. Whether it’s categorizing tasks by feature, department, or milestone, these metadata elements make it easier to filter and search for relevant tickets. By utilizing labels and tags effectively, you can improve organization and streamline ticket management within Jira.
Furthermore, consistent labeling conventions enhance collaboration and communication across teams. When everyone adopts a standardized approach to labeling tickets, it becomes simpler to locate specific tasks and understand their context. Moreover, labels and tags can provide valuable insights for reporting and analytics, enabling teams to track progress and identify trends over time.
Effective communication is the cornerstone of successful project management. Encourage team members to provide detailed updates, ask questions, and collaborate openly within Jira ticket comments. This transparent communication ensures that everyone stays informed and aligned, fostering a collaborative environment conducive to productivity and success.
Clear communication within Jira ticket comments keeps team members informed and facilitates knowledge sharing and problem-solving. Encouraging open dialogue enables team members to provide feedback, offer assistance, and address potential roadblocks promptly. Additionally, documenting discussions within ticket comments provides valuable context for future reference, aiding in project continuity and decision-making.
Identify repetitive tasks or processes and automate them using Jira’s built-in automation features or third-party integrations. This not only saves time but also reduces the likelihood of human error. By automating repetitive tasks, you can free up valuable resources and focus on more strategic initiatives, improving overall efficiency and productivity.
To ensure tickets are never missed, leverage Jira's automation capabilities to create rules for assigning and updating tickets. You can:
Additionally, keep stakeholders informed by setting up automated notifications. This ensures that everyone involved is aware of any changes or updates, reducing the risk of overlooked tickets.
For high-priority issues, implement escalation automation. This feature automatically alerts your team if important tickets remain unresolved beyond a specified timeframe, allowing you to address critical issues before they escalate further.
By combining these automation strategies, you can maintain a seamless workflow while ensuring that no ticket is left unattended.
Continuously reviewing your Jira setup and workflows is essential to identify areas for improvement. Solicit feedback from team members and stakeholders to understand pain points and make necessary adjustments. By regularly reviewing and refining your Jira configuration, you can optimize processes and adapt to evolving project requirements effectively.
Moreover, regular reviews foster a culture of continuous improvement within your team. By actively seeking feedback and incorporating suggestions for enhancement, you demonstrate a commitment to excellence and encourage team members to engage. Additionally, periodic reviews help identify bottlenecks and inefficiencies, allowing teams to address them proactively and maintain high productivity levels.
Jira seamlessly integrates with a wide range of third-party tools and services, enhancing its capabilities and extending its functionality. Integrating with other tools can streamline your development process and enhance collaboration, whether it’s version control systems, CI/CD pipelines, or communication platforms. Incorporating workflow automation tools into the mix further enhances efficiency by automating repetitive tasks and reducing manual intervention, ultimately accelerating project delivery and reducing errors.
Furthermore, integrating Jira with other tools promotes cross-functional collaboration and data sharing. By connecting disparate systems and centralizing information within Jira, teams can eliminate silos and improve visibility into project progress. Additionally, integrating with complementary tools allows teams to leverage existing investments and build upon established workflows, maximizing efficiency and effectiveness.
Encourage a mindset of continuous improvement within your software teams. Encourage feedback, experimentation, and learning from both successes and failures. By embracing a culture of constant improvement, you can adapt to changing requirements and drive greater efficiency in your Jira ticket management process while also building a robust knowledge base of best practices and lessons learned.
Moreover, fostering a culture of continuous improvement empowers team members to take ownership of their work and seek opportunities for growth and innovation. By encouraging experimentation and learning from failures, teams can cultivate resilience and agility, enabling them to thrive in dynamic environments. Additionally, celebrating successes and acknowledging contributions fosters morale and motivation, creating a positive and supportive work culture.
Customizing your Jira Service Management project is key to optimizing your workflow and ensuring your team operates efficiently. Here’s a guide to help you tailor your project for the best possible outcomes.
To stay on top of incoming requests, set up email notifications. As a project administrator, you can link a custom email account to ensure no request goes unnoticed:
Enhance your request management by configuring chat channels. This feature allows you to generate tickets directly from platforms like Slack or Microsoft Teams:
To get your team fully operational, add members to your project with the appropriate roles:
While these steps will set a solid foundation, consider further customizations such as adjusting request views, organizing queues, and setting up Service Level Agreements (SLAs) to match your team’s specific needs.
By following these guidelines, you’ll ensure that your Jira Service Management project is customized for maximum efficiency and productivity.
Jira is designed to streamline project management and problem-solving tasks. By leveraging its capabilities, various teams can maintain seamless operations. Here’s how Jira can be utilized:
Using Jira for ticketing enables teams to collaborate effectively, monitor tasks, and troubleshoot efficiently. By providing clarity and structure, Jira helps in swiftly navigating roadblocks.
Better JIRA ticket management helps in improving planning accuracy. Below are a few of the ways how these strategies can further help in better planning:
Improving your Jira ticket management, essential for effective task management, requires thoughtful planning, ongoing refinement, and a commitment to best practices. Implementing these tips and fostering a culture of continuous improvement can optimize your workflows, enhance collaboration, and drive greater project success, benefiting both internal teams and external customers.
To achieve these goals, consider how a robust ticketing system can transform your software team's operations:
By leveraging these capabilities, your team can streamline workflows and improve project outcomes, ultimately driving success across all facets of your software development process.
If you need further help in optimizing your engineering processes, Typo is here to help you.
Curious to know more? Learn about Typo here!
In Agile project management, it is crucial to get a clear picture of the project’s reality. Hence, one of the best ways is to visualize the progress.
A Burndown chart is a project management chart that shows the remaining work needed to reach project completion over time.
Let’s understand how can you create a burndown chart in Excel:
A Burndown chart visually represents teams’ or projects’ progress over time. It analyzes their pace, reflects progress, and determines if they are on track to complete it on time.
Burndown charts are generally of three types:
The product burndown chart focuses on the big picture and visualizes the entire project. It determines how many product goals the development team has achieved so far and the remaining work.
Sprint burndown charts focus on the ongoing sprints. It indicates progress towards completing the sprint backlog.
This chart focuses on how your team is performing against the work in the epic over time. It helps to track the advancement of major deliverables within a project.
A burndown chart has two axes: X and Y. The horizontal axis represents the time or iteration and the vertical axis displays user story points.
It is the diagonal line sloping downwards that represents the remaining work a team has at a specific point of the project or sprint under ideal conditions.
It is a realistic depiction of the team’s performance that is updated in real-time. It is drawn as the teams progress and complete user stories.
Each point on the work lines displays a measurement of work remaining at a given time.
It is the rightmost point of your burndown chart that represents whether the team has completed a project/sprint on time, behind, or ahead of schedule.
A Burndown chart helps in keeping an eye on teams’ work progress visually. This is not only simple to use but also motivates the team to perform well.
A burndown chart is useful to show the direct comparison between planned work and actual progress over time. This helps in quickly assessing whether the team is on track to meet its goals.
A burndown chart acts as a tool for inspiration. Such types of charts transparently show the progress and work efficiency. Hence, improving the collaboration and cooperation between team members.
A burndown chart must be updated daily. This helps in tracking progress in real-time, identifying problems in early stages hence, assisting in completing the project on time.
Open a new sheet in Excel and create a new table that includes 3 columns. This table will serve as the foundation for your sprint burndown chart.
Now, fill in the data accordingly. This includes the dates of your sprints and numbers in the Ideal Burndown column indicating the desired number of tasks remaining after each day throughout the, let’s say, 10-day sprint.
To do this effectively, start by clearly defining your planned tasks data. This data should reflect the number of tasks you expect to remain at the end of each day. Remember, this is your ideal work progression, and it won't account for unexpected delays or challenges.
Here’s a straightforward example to guide you:
It's crucial to update your actual tasks column daily as your team completes tasks. At the end of each day, record the number of tasks remaining. This will give you an accurate picture of how your team is progressing compared to your plan.
By maintaining this discipline, you’ll be able to adjust your strategy and resources in real time, ensuring your project stays on track.
As you complete tasks each day, update the spreadsheet to document the number of tasks you can finish under the ‘Actual Burndown’ column.
Now, it’s time to convert the data into a graph. To create a chart, follow these steps: Select the three columns > Click ‘Insert’ on the menu bar > Select the ‘Line chart’ icon, and generate a line graph to visualize the different data points you have in your chart.
Study project scope and divide the projects or sprints into short-term tasks. Ensure to review them and estimate the time required to complete each task based on the project deadline.
The Scrum master must check the chart often and update it daily. It helps to understand the flagging trends, know the pitfalls, and ensure it aligns with the expectations.
Don’t lose sight of the outcome. By focusing on it, software development teams can ensure they are making progress toward their goals and adjust their efforts accordingly to stay on track for successful project completion.
Teams pause the work during weekends or holidays. Excluding weekends provides accuracy by focusing solely on the days when active work is being done hence giving a clearer representation of progress and highlighting the team’s actual productivity levels during working days.
Burndown chart, when accessible to the entire team, fosters collaboration and accountability. It gives them a sense of ownership to discuss points to address challenges and celebrate achievements.
A burndown chart is great for evaluating the ratio of work remaining and the time it takes to complete the work. However, relying solely on a burndown chart is not the right way due to certain limitations.
Although creating a burndown chart in Excel is easy, entering data manually requires more time and effort. This makes the work repetitive and tiresome after a certain point. Fortunately, there are various tools available in the market that offer collaboration and automation features, including Jira, Linear, Trello, and Asana, which streamline this process significantly.
These tools allow for real-time progress tracking, where updates to burndown charts happen automatically as tasks are completed, saving hours that would otherwise be spent on manual input. This automation not only saves time but also reduces the risk of human error, ensuring that your reports are always accurate and up-to-date.
The Burndown chart helps in tracking the progress of completing tasks or user stories over time within a sprint or iteration. But, it doesn’t provide insights about the specific types of issues or tasks being worked on, such as shipping new features or determining technical debt. This is where advanced project management tools shine.
They offer visual reports and overviews that give you a birds-eye view of project health, timelines, and workload distribution. This comprehensive insight is something a simple Excel spreadsheet cannot match.
A burndown chart doesn’t differentiate between an easy and difficult task. It considers all of them equal, regardless of their size, complexity, or effort required to complete it. Hence, leading to ineffective outlines of project progress. This further potentially masks critical issues and hinders project management efforts.
Project management tools address this by providing task management features with customizable boards and views, allowing you to assign varying weights and priorities to tasks. This approach ensures a more accurate reflection of project status and helps in identifying bottlenecks before they escalate.
As a result, the burndown chart is not a reliable metric engineering leaders can solely trust. It is always better to complement it with sprint analysis tools to provide additional insights tailored to agile project management. A few of the reasons are stated below:
Moreover, these tools often support collaboration features, such as built-in chat and video meetings, keeping all communication linked to tasks and ensuring transparency across the team. With mobile and remote access capabilities, they enable project management on the go, maintaining team alignment whether you're in the office or working remotely.
Typo’s sprint analysis feature allows engineering leaders to track and analyze their team’s progress throughout a sprint. It uses data from Git and the issue management tool to provide insights into getting insights on how much work has been completed, how much work is still in progress, and how much time is left in the sprint hence, identifying any potential problems early on and taking corrective action.
Martin Fowler once said “Anyone can write a code that a computer can understand. Good programmers write code that humans can understand.”
Clean code is an essential component of software development.
Writing clean code is exactly like a sales pitch. When you use words full of technical jargon, you end up losing your target audience. The same is true with coding as well. Writing clean code enhances the readability, maintainability, and understandability of the software.
Robert C. Martin in his book “Clean Code: A Handbook of Agile Software Craftsmanship“ defined clean code as:
“A code that has been taken care of. Someone has taken the time to keep it simple and orderly. They have laid appropriate attention to details. They have cared.”
Clean code is clear, understandable, and maintainable. It is well-organized, properly documented, and follows standard conventions. The purpose behind clean code is to create software that is not just functional but readable and efficient throughout its lifecycle. Since the audience isn’t a computer but rather a real live audience.
Clean code is the foundation of sustainable software development. Below are a few reasons why clean code is important:
Technical debt can slow down the development process in the long run. Having clean code ensures that future modifications will be smoother as well as less costly process.
Clean code means that the developers are prioritizing clarity. When it is easier to read, understand, and modify code, it leads to faster software development.
Good code means that the code is accessible to all team members and follows coding standards. This helps in improved communication and collaboration among them.
Clean code is designed with clarity and simplicity. Hence, making it easier to locate and understand specific sections of the codebase. This further helps in identifying and resolving issues in the early stages.
Clean code facilitates unit testing, integrated testing, and other forms of automated testing. Hence, leading to increased reliability and maintainability of the software.
Below are some established clean code principles that most developers find useful.
Apply the KISS (Keep it simple, stupid) rule. It is one of the oldest principles of clean code. This means that don’t make the code unnecessarily complex. Make it as simple as possible. So that it takes less time to write, has less chance of bugs, easier to understand and modify.
This law states that the entity (class, function, or variable) must have a single, defined goal. It should only do one thing in one circumstance.
DRY (Don’t repeat yourself) is closely related to the KISS rule and Curly’s law. It states to avoid unnecessary repetition or duplication of code. Not following this can make the code prone to bugs and make the code change difficult.
YAGNI (You aren’t gonna need it) rule is an extreme programming practice that states that the developers shouldn’t add functionality unless deemed necessary. It should be used in conjunction with continuous refactoring, unit testing, and integration.
It means that the code should fail as early as possible. This is because issues can be quickly identified and resolved which further limits the number of bugs that make it into production.
This rule by Uncle Bob states that always leave the code cleaner than you found it. It means that software developers must incrementally improve parts of the codebase they interact with, no matter how minute the enhancement might be.
Apply the SOLID principles. This refers to:
S: Single Responsibility Principle which means that the classes must only have a single responsibility.
O: The open-closed Principle states that the piece of software should be open for extension but closed for modification.
L: The Liskov Substitution Principle means that subclasses should be able to substitute their base class without getting incorrect results.
I: The Interface Segregation Principle states that interfaces should be specific to clients instead of being generic for all clients.
D: The dependency Inversion Principle means that classes should depend on abstractions (interfaces) rather than concrete implementations.
A few of the best practices include:
Choose descriptive and clear names for variables, functions, classes, and other identifiers. They should be easy to remember and according to the context that conveys the purpose and behavior to make the code understandable.
Most programming languages have community-accepted coding standards and style guides. Some of them include Google Java style and PEP 8 for Python and Javascript. Organizations must also have internal coding rules and standards that provide guidelines for consistent formal, naming conventions and overall code organization.
Comments help explain the code. However, the codebase changes continuously so the comment can become old or obsolete soon. This can create confusion and distraction among software developers. Make sure to keep the comments updated. Also, avoid writing poorly written or redundant comments as it may increase the cognitive load of software engineering teams.
Magic numbers are hard-coded numbers in code. They are considered to be a bad practice since they can cause ambiguity and confusion among developers. Instead of directly using them, create symbolic constants for hard-coded values. It makes it easy to change the value at a later stage and improves the readability and maintainability of the code.
Ensure that you regularly refactor to enhance the structure and readability of the code. It also helps in improving its flexibility and maintaining code that is overly complex, poorly structured, or duplicated.
You can apply refactoring techniques such as extracting methods, renaming variables, and consolidating duplicate code to keep the codebase cleaner.
Version control systems such as GIT, SVN, and Mercurial help track changes to your code and pull back to previous versions, if necessary. Before refactoring, ensure that the code is under version control to safely experiment with changes. Moreover, it helps understand the evolution of the project and maintains the integrity of the codebase by enforcing a structured workflow.
Software developers can write unit tests to verify the code’s correctness as well-tested code is reliable and easier to refactor. Test-driven development helps in writing cleaner code as it considers edge cases and provides immediate feedback on code changes.
Code reviewing continuously helps in ensuring code quality by identifying potential issues, catching bugs, and enforcing coding standards. It also facilitates collaboration between software developers to see each other’s strengths and review mistakes together.
Typo’s automated code review tool not only enables developers to catch issues related to code maintainability, readability, and potential bugs but also can detect code smells. It identifies issues in the code and auto-fixes them before you merge to master. This means less time reviewing and more time for important tasks. It keeps the code error-free, making the whole process faster and smoother.
Key features:
Writing clean code isn’t just a crucial skill for developers. It is an important way to sustain software development projects.
By following the above-mentioned principles and best practices, you can develop a habit of writing clean code. It will take time but it will be worth it in the end.
Hope this was helpful. All the best!
Dead code is the most overlooked aspect of software development projects. They can become common when they evolve. A large amount of dead code can be harmful to software.
The best way to ensure this is to detect dead code in the early stages to maintain the quality of the software application.
Let’s talk more about dead code below:
Dead code can be referred to as the segment of code that is unnecessary for the software program. They are executed without their results being used or accessed.
Dead code is known as zombie code. Such a portion of code may have been part of earlier versions, experimental features, or functions that are no longer needed. If the dead code remains in the software, it can decrease the software’s efficiency and add unnecessary complexity to it. This can further make the code harder to understand and maintain.
The segment of code that is never executed under any condition during program runtime. It could be due to conditional statements, loops, or other control flow structures. Besides this, the issue may even arise during development because of coding errors, incorrect logic, or unintended consequences of code refactoring.
The portion of code that was once useful but not anymore. They have now become outdated or irrelevant due to changes in software requirements or function, technology, or best practices. Obsolete code may still be present in the codebase however, no longer recommended for use.
Code that was once part of a functional feature or system but is now left behind or isolated. This can result from changes in project requirements, refactoring, feature removal, or other modifications in the development process. As obsolete code, this code may still be present but no longer integrated or contribute to the application functionality.
Sometimes, developers ‘comment out’ code rather than deleting it to use it in the future. However, when they forget about it, it can facilitate dead code. While it is a common practice, developers must take note of it otherwise it can reduce code readability and maintainability.
Dead code majorly contributes to Technical Debt. While a small amount of technical debt is still fine, if it grows, it can negatively affect the team’s progress. This can also increase the delivery time to market to end-users and reduce customer satisfaction.
Hence, it is important to monitor technical debt through engineering metrics to take note of dead code as well.
Besides this, there are other reasons why removing dead code is crucial:
When dead code is present, it can complicate the understanding and maintenance of software systems. It can further lead to confusion and misunderstandings which increases the cognitive load of the engineering team.
Eliminating dead code lets them focus on relevant code that helps increase code readability, and facilitates feature updates and bug fixes.
Dead code could be a hidden backdoor entry point to the system. This can be a threat to the security of the software. Moreover, dead code includes dependencies that are no longer needed.
Removing dead code simplifies code complexities, and improves code review and analysis processes. This further helps to address and reduce security vulnerabilities easily.
Dead code disrupts the understanding of codebase structure. It not only decreases the development process but also developers’ productivity and effectiveness.
Eliminating dead code results in reducing the overall size of the code. Hence, it makes it concise and easier to manage which potentially enhances developers’ performance.
Duplicate code is a considerable strain on the software development process. However, when dead code is present, it diverts developers from identifying and addressing areas where code duplication occurs.
Hence, eliminating dead code avoids code duplication and improves the codebase’s quality.
When dead code is not present in the software, it allows developers to focus on the relevant active parts of the codebase. It also streamlines the process as there are no unnecessary distractions and identifies and addresses issues.
Dead code can often be removed through static code analysis tools. Automated tools such as code quality checkers can help in detecting unused variables, classes, imports, or modules. This allows developers to address and eliminate the dead code easily which reduces the development cost and improves the overall quality of the system.
However, the drawback is that during uncertainty regarding programming behavior, dead code may not be removed. Hence, static code analysis tools are not a complete solution.
Dynamic code analysis tools involve running the program to see which lines are executed and identifying which code paths are never reached. Hence, the code that is never executed or used in the codebase i.e. dead code is eliminated.
However, most of these tools are specific to programming languages.
Leverage version control systems such as GIT commits to identify code that was once active but now deprecated or replaced. Commits that were removed or modified could indicate areas where dead code be found.
In case of a mistake, the code can be retrieved from the version control system. Hence, less risky and easily manageable.
Through refactoring, developers carefully examine the codebase to identify sections that include unused or old code, unnecessary variables, functions, or classes. Hence, revealing dead code that can be safely removed. Moreover, refactoring aims to optimize code for performance, maintainability, and readability. This further allows developers to look out for inefficient or unnecessary code by replacing or redesigning these segments.
Code review is an effective method to maintain the quality of code. It promotes simplicity and clarity in the codebase. They can help in detecting dead code by applying best practices, standards, and conventions. However, when not automated, they can be time-consuming and harder to implement. Hence, it is recommended to use automated code review tools to speed up the process.
Typo’s automated code review tool identifies issues in your code and auto-fixes them before you merge to master. This means less time reviewing and more time for important tasks. It keeps your code error-free, making the whole process faster and smoother.
Key features:
In software engineering, detecting and removing dead code is imperative for streamlining the development process. You can choose the method or combination of methods to remove dead code that best aligns with your project’s needs, resources, and constraints.
All the best!
Time is a finite resource. Once it is gone, you cannot alter it.
This is why the calendar plays a major role in organizing and focusing towards our goals. However, it can become cluttered and overwhelming, when done incorrectly. It not only affects the engineering teams but also impacts business and client experience negatively.
Hence, the optimization of calendars is important for both engineering managers and developers.
In this blog, let’s dive further into the art of calendar optimization and various time management techniques.
Optimizing your calendar means making the most of your working hours. Effective time management allows you to create a micro plan for the day ahead and focus on high-priority tasks. Managing your time effectively reduces the risk of burnout and stress; helping in great productivity and alignment.
Another importance of optimizing your calendar is that it helps in defining the project goals. When they are clearly outlined, it lets you align your schedules with the project needs. Breaking them down into smaller tasks lets you focus on them more effectively and tackle critical tasks first.
Creating a daily schedule empowers you to spend more time on the project that matters and capture bigger opportunities. This further helps in prioritization and taking control of your day. Hence, reduces distractions and empowers you to do deep work.
Another benefit of optimizing your calendar is achieving a work-life balance. You and your team get time for both personal and professional tasks. This helps in becoming more productive and reduces stress and feeling overwhelmed throughout the day.
When your priorities are set and have a clear schedule, it helps you deliver high-quality commits on time. It makes your team reliable and improves their professional reputation which further helps in their career growth.
In 2009, Paul Graham (co-founder of Y-Combinator), coined the terms – Maker schedule and Manager schedule. These are two different styles of working that require different approaches.
Let’s understand both these terms in detail:
The maker schedule is designed for individuals who need long, uninterrupted slots for focus time. It allows them to enter into the state of flow to achieve peak productivity. For the developers who require deep concentration, this type of schedule lets them fully immerse in projects and let the creativity flow.
First things first, create a to-do list. See which tasks need to be done solo and which need to be collaborated. Now, prioritize them according to their due dates. Communicate with other team members for the collaborative tasks.
Set a specific time for deep work. You can add more than one per day since the tasks can stretch further. Use shorter blocks for meetings, communication, and other administrative tasks. Ensure that you communicate with others to minimize interruptions and distractions.
Bunch meetings such as team meetings, and one-on-one conversations together. However, schedule a 5-minute break between these meetings. This can reduce context switches and let you enter into a specific mental state. Hence, helps you with better concentration and productivity.
Don’t forget to take short breaks between your slots. This can be anything ranging from short naps to exercise. This helps in maintaining focus and better retention of information. As a result, it increases your energy and prevents burnout.
The manager schedule is for individuals who have various duties while handling teams and systems. It is usually for engineering managers and leaders since their day comprises meetings, managing teams, and their solo tasks as well. Their schedule is majorly based on coordinating with people who produce output. Hence, the schedule needs to be flexible yet maintain structure in their workflow.
Ensure that your meetings have clear goals and objectives. This helps minimize time wastage and keep discussions on track. Also, note that the meetings should be purposeful with a time limit. So, that they are straightforward and crisp.
Maker’s and manager’s schedules can contradict each other. Hence, have open communication about each other’s schedules. This allows everyone to not interrupt each other’s focus time and other important schedule. As a result, it reduces stress and pressure.
Make sure that you integrate your personal calendar as well so that your team knows when you are not available. It saves you and your team members from the trouble of rescheduling and streamlining planning without any stress.
Regularly review your schedule and adjust it accordingly. Check what’s working for you, and what can be delegated and eliminated. Align your time with evolving priorities and communicate the same with your team members.
In the current scenario, the maker schedule is difficult to follow in the organization. The culture is still meeting-heavy and prioritizes urgent and reactive tasks over deep work.
Below are a few of the ways to balance both approaches:
As the manager and maker schedules are different, async communication works better in this case. Tools like Slack and Microsoft Teams bridge the gap between these two frameworks. It creates an ecosystem where deep and creative work is prioritized yet allows you to be in regular contact with your team members without interruptions.
Meetings that don’t have clear agendas and comes between your team members’ schedule need to be assessed. Review them regularly so that you know which of them are overlapping and can disrupt the workflow.
To make it easier to assess, you can ask yourself three questions:
It is important to understand that creativity doesn’t always come at office hours. It can occur at different times and manners. Hence, communicate with your team members what are their focus time slots. A flexible schedule also allows them to respond to you at their convenient time while maintaining overall balance.
Synchronization is important for both schedules. In these cases, creating a feedback loop to discuss scheduling and priorities. Encourage open communication to see what works for you as well as for others. This lets team members have mutual understanding, empathy, and respect for each other’s roles and working styles.
Even after balancing the schedules, developers may still not have time to complete all their tasks.
Below are a few of the time management techniques you can experiment with:
This technique was coined by Dwight Eisenhower. This framework is specially built for individuals in leadership positions such as engineering managers, tech leads, and heads of engineering.
This time management technique helps to prioritize tasks based on urgency and importance.
It includes four separate quadrants:
This technique was developed by David Allen to make your tasks into a straightforward to-do list and break them down into actionable work items. It is a 5-step method that includes:
Getting things done helps developers if they feel overwhelmed and struggle to focus on a single task.
This time technique is an 80/20 rule created by Vilfredo Pareto. This states that 20% of our actions are responsible for 80% of outcomes. It allows you to prioritize tasks that are most effective at solving problems.
This can be done by:
This time management technique was created by Francesco Cirilio. It creates a sense of urgency and focus on a single task without interruptions.
In this technique:
This helps to eliminate burnout and improve performance and productivity.
Created by Taiichi Ohno, the main idea behind this visual time-tracking technique is to improve overall productivity and effectiveness. It helps to plan effectively, create SMART goals, and proper task delegation.
You have to:
There is no one-size-fits-all template for this technique. You can customize it according to your preferences and team size.
Optimizing the calendar is most important for engineering teams. They have a lot on their plate and have different working styles which allow them to create their best schedules and communicate with their team members.
Typo, an engineering management platform, allows engineering leaders to gain visibility on the team’s efficiency and workload. Book your demo and level up your developer game today!
Code Smells - A common encounter by developers and testers.
They are tangible and observable evidence that something is wrong with the application's underlying code. When left unaddressed, it can degrade the application's performance and increase the technical debt. This further makes it difficult for the software teams to provide value over time and deliver the product faster to the market.
Code Smell was first introduced by Kent Back in the 1990s and popularized by Martin Fowler’s Refactoring Book.
In simple words, code smell is a warning that the source code is messy and isn’t meeting the best practice standards.
However, Code Smell isn’t synonymous with bugs or errors. And they do not always mean that the code is wrong or broken. It highlights the presence of bottlenecks in the codebase that need immediate attention. If not, they can reduce the code quality, readability, and maintainability.
Moreover, Smelly code can easily become rotten code, when not taken care of in early stages. One of the main causes of code rot is technical debt. Hence, it is advisable to periodically check and fix them to prevent both code rot and technical debt.
Code refactoring is a crucial strategy to counteract these issues. It involves restructuring existing code to enhance its quality while maintaining its core functionality. As defined by experts such as Kent Beck, refactoring is a change that leaves the system's behavior unchanged, yet improves nonfunctional qualities like simplicity and flexibility. Martin Fowler adds that refactoring makes the internal structure of software easier to understand and cheaper to modify.
Benefits of Refactoring:
Testing and Refactoring: It’s essential to ensure complete test coverage before embarking on refactoring. This guarantees that the functionality remains intact, safeguarding code quality.
Incorporating these practices will help maintain the integrity of your code and prevent the pitfalls of neglect, such as code rot and mounting technical debt.
In software development, code smells are indicators of potential issues in the codebase that may hinder maintainability and readability. Understanding and addressing these common code smells can significantly improve your software quality.
Duplicated code is the most common code smell. It happens when a similar code exists in more than one area, often due to copying and pasting in different parts of the program. Although it may look harmless, it becomes challenging since the developer has to make multiple tweaks during feature updates. This not only decreases code maintainability but also results in inconsistent applications, as the change wasn’t applied uniformly. It further increases the cycle time and poses a business risk as well.
The long method is when the method contains too many lines of code. There isn’t any specific number of lines that are considered long. Some believe it to be 25, while others think 50 is too long. This code smell also violates the single responsibility principle. Long methods make adding new features or updating existing ones challenging. It becomes harder to test, understand, and debug the code. This not only increases the cyclomatic complexity but also leads to unexpected bugs.
Dead code occurs when developers forget to clean up existing code, aren’t aware of the dead code in the first place, or leave behind old, commented-out code. The code is no longer needed yet is still present in the application. It can be a variable, parameter, field, method, or class. The amount of dead code in the application signifies how well projects were managed, how much the team cares about technical debt, and the level of communication between them. This makes code hard to understand and increases bugs, errors, and security vulnerabilities.
This code smell arises when a class exists yet doesn’t contribute significantly to the function or behavior of the software. This increases code complexity and clutters the code base, thereby increasing the cognitive load for developers, which costs both time and money. If left unaddressed for a long time, it can result in future risks, such as adding more functionality to the lazy class, leading to a bloated or poorly designed class.
The Middle Man occurs when a class delegates work to another class and doesn’t have any independent functionality. A few reasons behind this code smell include previous refactoring that may have moved functionality elsewhere, leaving the class empty, or a middle man that was relevant at one point but is no longer needed. This increases code complexity and creates noise in the codebase, making it harder to maintain the code and less efficient without adding significant value.
Primitive obsession is a type of code smell that developers can’t identify intuitively. It occurs when a primitive value controls the logic in a class and represents complex concepts or behaviors. In simple words, it happens when code relies too much on primitive values. Using primitives for everything leads to poor readability, validation, and abstraction.
God objects are one of the most common and problematic code smells. It occurs when a single class or program is central to the system, handling diverse tasks that are not cohesively related. It violates the single responsibility principle and creates tight coupling and challenges in code maintenance. God objects use more unwanted resources even for simple operations and make it difficult to isolate and test components effectively.
This code smell arises when a class accesses the data or method of another class more than its own. It happens because the class’ functionality is too closely tied to another class. Feature envy violates the ‘Law of Demeter,’ which states that objects should only talk to their immediate friends and not access the internal data and methods of other objects. It can indicate a poor design that doesn’t include the encapsulation and cohesion of objects, leading to high coupling between classes.
A large class contains many fields, methods, lines of code, or responsibilities, violating both the single responsibility principle and the open-closed principle. It indicates a weakness in the design and makes it difficult for developers to understand, read, and maintain the code. Moreover, it increases the chances of errors and makes it harder to locate them. Note that God objects often manifest as large classes; however, not all large classes are god objects.
Improper names of variables, classes, and functions indicate that the code is not clean. This could happen when it includes overly abbreviated names, non-descriptive names, or using different name schemes. This leads to an increase in the cognitive load of developers and causes ambiguity, lacking precision, and leading to more confusion and errors. Besides this, improper names make pair programming and knowledge sharing challenging for developers.
Unfortunately, comments are code smells too. While it is a good practice, when overused for every step, it creates excessive noise in the code. This decreases readability and maintainability. Comments can be inaccurate, as they are often based on the reviewer’s perspective and understanding. Comments should only explain the ‘Why’ and ‘What it is doing’ parts of the code, not the ‘How’ it works. If this is necessary, the code might not be self-explanatory and could require refactoring. Besides this, long, dense blocks of text can disrupt the visual flow.
A long parameter list occurs when there is a long list of parameters in a method or class. Usually, the maximum number of parameters in a method should be 3 or 4. Otherwise, it tries to handle too many responsibilities. It decreases readability and reusability and makes the code prone to errors and bugs. It further makes testing harder and debugging difficult. Besides this, it can become challenging to reuse the method in different contexts since it might require specific combinations of parameters.
Shotgun surgery happens when developers have to make lots of small changes to the codebase. The code smell often overlaps with other code smells, especially duplicate code. It might be scattered around a much larger class or may even be in multiple classes or different parts of the codebase. This type of code smell forces a clumsy, error-prone approach and unnecessarily adds complexity to the codebase. The changes consume more time and increase the cognitive load of developers since they have to remember the changes in various places.
Inappropriate intimacy occurs when a method has too much intimate knowledge of another class or method’s inner workings or data. It means bi-directional behavior between classes that are tightly linked to each other. Changes in one module can easily break the other due to their deeply intertwined nature. This results in difficulty in enhancing/extending features and fixing bugs. Inappropriate intimacy also reduces modularity, flexibility, and testability.
By identifying and addressing these common code smells, developers can enhance code quality, maintainability, and efficiency, leading to a more robust and scalable software system.
Understanding Data Clumps
Data clumps are bundles of related data items that tend to appear together across different parts of a codebase. This might be seen as fields across several classes or as parameters frequently used together in multiple functions. When certain pieces of data constantly travel as a group, it can become difficult to manage their behavior effectively across the application.
The presence of data clumps makes a codebase less flexible and more prone to errors. When a particular data item is only meaningful as part of a group, rather than on its own, it’s a strong indicator of a data clump. This "code smell" signals that the data should be refactored to improve maintainability and clarity in the code.
Managing Data Clumps
By addressing data clumps promptly, developers can maintain a clean, efficient, and manageable codebase. Implementing these refactoring techniques helps keep code logical and reduces the complexity that data clumps can introduce.
Code smells, while easily overlooked, can significantly affect the long-term health of your software. By adopting proactive strategies, teams can mitigate these issues early on. Here are the top ways to avoid code smells in your development process:
Regular code refactoring remains one of the most effective methods to dodge code smells. This process involves fine-tuning your code for clarity and efficiency without altering its external behavior. By refining the internal structure of your code, you ensure it remains understandable, adaptable, and high-performing.
Why It Works:
When to Refactor:
Tools to Consider:
CI/CD practices enable seamless tracking and integration of code changes, ensuring that issues are caught promptly. By continuously integrating small changes and immediately testing them, you minimize the risks of code smells emerging.
Benefits:
By automating the build and testing processes, you ensure any potential smells are immediately flagged and addressed.
Automated code reviews act as a safeguard, highlighting potential code smells that might have been missed during development. While traditional peer reviews are thorough, they can be time-consuming and inconsistent.
Advantages of Automation:
Popular Tools Include:
By incorporating these key strategies into your development process, you ensure that code remains robust, adaptable, and free from detrimental impurities that can accumulate over time.
Continuous Integration (CI) plays a crucial role in maintaining high code quality and reducing the presence of code smells. But what exactly does it do?
1. Automating Testing:CI tools like Jenkins, Travis CI, and GitLab CI/CD automate the process of running tests on new code changes. By doing this, developers can immediately identify issues, enabling them to fix code smells before they propagate.
2. Incremental Code Integration:Developers are encouraged to integrate small chunks of code frequently. This incremental approach helps in pinpointing specific sections where code smells may arise, making it easier to resolve them promptly.
3. Immediate Feedback Loop:When code changes are integrated, CI systems provide instant feedback. This swift response minimizes the risk of code smells by allowing developers to address problems as soon as they arise, rather than letting them fester.
4. Consistent Code Quality:Through automated checks, CI helps enforce coding standards across a team, ensuring that any deviation is quickly addressed. This consistency is key in preventing code smells, which often emerge from overlooked standards or practices.
5. Enhanced Collaboration:With CI, any code modification made by team members is visible and trackable. This transparency fosters better collaboration, enabling peer reviews and discussions that often lead to identifying and resolving code smells early on.
Ultimately, Continuous Integration not only accelerates the development process but actively works to maintain clean, efficient, and high-quality code by quickly catching potential issues before they escalate.
A code smell is a common problem faced by developers, indicating the potential issues within a codebase. It is important to address them in the early stages, otherwise, it can reduce the code quality and slow down the entire development process.
Detect these code smells with Typo’s automated code tool which enables developers to catch issues related to maintainability, readability, and potential bugs. It identifies issues in the code and auto-fixes them before you merge to master. This means less time reviewing and more time for important tasks. It keeps the code error-free, making the whole process faster and smoother.
Key features:
Code review helps you to improve the quality and maintainability of your code. However, this process is challenging for both engineering managers and developers. While managers need to perform thorough reviews to ensure code quality, developers are usually overwhelmed when receiving feedback.
Engineering managers need to be courteous and respectful while offering constructive feedback to their developers. They must be clear with their feedback so that developers can understand your feedback in the right way and not take it negatively.
In this blog post, let’s explore the ways to provide code review feedback to developers:
Also known as peer review, code review is a key practice within quality assurance. It is a systematic examination of a software code by one or more individuals to improve its quality, identify issues, and ensure that it aligns with established coding standards and best practices.
Code reviews allow engineering managers and developers to detect issues and bugs in the early stages. So that the problems can be fixed before the end-users see them. Besides this, It allows developers to work with fresh knowledge, or else they may struggle to remember code, solutions, and reasoning.
Reviewing code regularly allows developers to learn more reliable techniques and best practices. It helps in gaining valuable insights into diverse coding styles and problem-solving approaches. Code review also allows engineering managers to mentor junior developers and foster a culture of continuous learning and growth.
Regular code reviews ensure the entire team adheres to consistent coding standards and best practices. This makes it easier for developers to understand and contribute to the codebase. Hence, they can write more readable and maintainable code over time. Besides this, it provides opportunities for refactoring.
Optimizing code through the code review process eliminates a significant amount of technical debt. It also detects code smells which are early signs of potential technical debt. Code reviews analyze the code and catch bugs to reduce the need for extensive rework later.
Always ask questions rather than demanding changes. It not only opens up a dialogue but also lets them think about input without being defensive. This also ensures that both parties can decide on the right course of action and know each other's perspective. When asking questions, developers can explain their thought process and rationale behind the code. This also fosters a culture of collaboration and highlights that nobody is always right.
Instead of saying ‘Change the variable name’, ask ‘I see you named this variable ‘Temp’. What about calling this variable ‘UserID’?
It is seen that written constructive feedback is usually taken negatively. Since the individual cannot see the body language, facial expressions, or tone of the other person. Words like just, easy, and obvious may seem belittling to the developers. This not only diminishes confidence but also introduces ambiguity within the team.
Make sure that you provide feedback in clear and complete language. And most importantly, Be polite!
This will help developers grow and work efficiently. Hence, enhancing overall code quality.
Don’t say ‘This fix is way too easy’. Instead, use this ‘I see a straightforward implementation here. Can you walk me through your decision-making process?’
Address the code directly rather than the developer. Discuss what can be improved in the code, not the developer’s skills or characters. Blaming them will lead to judgments, rejections, and defensiveness. They would avoid taking feedback positively.
Hence, ensure an objective evaluation of the code. Make this process a team sport and focus only on facts.
This will not affect any interpersonal relationships within the team and developers will take feedback seriously.
Instead of saying ‘You haven’t optimized the code efficiently’, You can say ‘This code hasn’t been optimized properly’.
Instead of just telling what improvements to be made to pull requests or code, explain the reason behind the change. Let developers know about the thought process and reasoning so that they look from the other’s perspective. Add a brief explanation along with the change mentioned.
Never assume that developers understand the ‘Why’ behind the change. Always clarify the reason so that they know where it is coming from.
This will help developers improve their skills and knowledge, enhancing code quality.
Don’t say ‘Update the variable names’. Instead, say this ‘Try adding descriptive variable names to enhance code readability and make it easy for other developers to collaborate and maintain the codebase.’
Clarify to developers that it is not a universal statement or generalization. Rather, it’s an observation or one perspective as per the code written.
Hence, use ‘I’ while writing constructive feedback. It not only fosters an open and receptive environment for discussing code changes and improvements but also makes it easier for both sides to look for solutions.
This makes developers less defensive about their work and more open to pair programming and learning opportunities.
‘The code is hard to follow’ should be changed to ‘I am finding this flow of code a bit challenging to follow.’
Always suggest solutions and guidance on how they can improve. It could be a framework, method, or API. It doesn’t mean giving a complete solution but sharing an improvement strategy. This will save developers time in implementing these suggestions and address issues (which they might have overlooked). Also, they will be able to learn new techniques, best practices, and coding standards to improve their coding skills.
Use examples as well so they understand the solution practically.
If the loop structure is inefficient, suggest a solution like ‘Consider using a 'for-each' loop instead of a 'for' loop for better readability and concise code.’
Apart from solutions, share learning resources with them. It could be related to the areas where developers need improvement, new industry trends, or code review best practices. It will help them stay updated with the current trends and improve their understanding of specific technologies and frameworks. Resources such as relevant documentation, tutorials, and online courses work wonders.
This will help developers take ownership of their learning and foster a sense of autonomy.
Instead of simply pointing out the developer’s blindspot, for example - Not familiar with the new framework’s syntax. Write this - ‘I noticed some challenges with the syntax of the new framework. I recommend checking this document ‘Framework Documentation.’ as it provides clear examples and explanations.’
Review code frequently as it reduces the need to make the process lengthy. Long code reviews would be overwhelming and confusing for developers since they need to make a lot of changes and improvements altogether. Even after doing it frequently, the code reviews take hours, break it down into small parts.
Smaller code reviews allow developers to understand the reason behind the constructive feedback. Hence, they can make changes to the code without any dilemma or misunderstanding.
Suppose a developer has submitted a large pull request that considers various features and changes.
Instead of sharing feedback all at once, say this ‘Let’s first focus on the changes related to the new feature implementation. Once done, we can move on to reviewing the improvements in the existing code.’
Effective code reviews take place when both positive and constructive feedback is included. Developers may make a few mistakes here and there. But, this doesn’t come from a bad place. They are improving, growing, and giving their best.
Hence, pat their backs on the things they have done correctly. Positive feedback creates a culture of recognition and gratitude which improves collaboration and communication.
This also lets development teams to continue put efforts and strive for excellence.
When recognizing their efforts, say this ‘Nice job on the new feature. Your attention to detail and writing readable code is commendable.’
Use code review tools to help in assessing the quality of code. These tools can help in spotting bugs and vulnerabilities, detecting code smells, syntax errors, security vulnerabilities, and many more. It also gives visibility into changes, hence, making the feedback more focused and contextually relevant.
These tools also ensure that the code adheres to the coding standards and best practices.
Typo’s automated code review tool identifies issues in your code and auto-fixes them before you merge to master. This means less time reviewing and more time for important tasks. It keeps your code error-free, making the whole process faster and smoother.
The code review process might be time-consuming, but, it is rewarding too. It helps in knowing whether the code needs refactoring, has bugs or errors, or anything else that could hamper its performance.
Follow the 10 tips mentioned above to encourage collaboration, open communication, and knowledge sharing among developers.
Happy reviewing!
Product Management and Software Engineering are among the roles that drive innovation for a product. And today, these roles are intertwined in ways that responsibilities and capabilities can seem blurred – which leads to the question, which role is right for you?
Product Managers answer the “why” and “what” questions about a product, while the Software Engineers answer the “how” – both important in software creation.
Choosing between product management and Software Engineering can be challenging since they are crucial for businesses. To help you make an easy decision, in this blog, we break down their roles, career responsibilities, trajectories, differences in day-to-day work, and where they are similar. Let’s dive in!
The Product Managers serve as the guiding strategic navigators of innovation and steer products from a mere idea, conceptualize it, and take it all the way to market launch. They provide the blueprint for the product’s path from inception.
Unlike Software Engineers, the Product Manager role extends beyond coding. They combine business acumen, technological insights, and customer-centric thinking and translate into the fulfillment of a product.
They deep dive into market analysis and identify user needs, effectively shaping the product roadmap. With this information, Product Managers align customers with business objectives. The product role also includes fostering a collaborative culture between engineers, designers, sales, and marketing teams while staying true to ever-changing market dynamics through agile methodologies.
They drive teams toward a shared goal while crafting a roadmap.
The Product Managers serve as the guiding strategic navigators of innovation and steer products from a mere idea, conceptualize it, and take it all the way to market launch. They provide the blueprint for the product’s path from inception.Unlike Software Engineers, the Product Manager role extends beyond coding. They combine business acumen, technological insights, and customer-centric thinking and translate into the fulfillment of a product.They deep dive into market analysis and identify user needs, effectively shaping the product roadmap. With this information, Product Managers align customers with business objectives. The product role also includes fostering a collaborative culture between engineers, designers, sales, and marketing teams while staying true to ever-changing market dynamics through agile methodologies.
They drive teams toward a shared goal while crafting a roadmap.
A Software Engineer evolves from an entry-level position to senior and staff levels. This path can lead them to management roles. They can manage engineering teams and progress to positions like VP of Engineering, CTO, and Director.
However, through this transition, they must develop varied skills to support their growth. From purely technical skills, their role can evolve to people management, a distinct skill honed over time.
Product Managers also grow similarly in their career paths. They move from being individual contributors to leading fellow Product Managers. It often involves market research and product marketing. Their trajectory then moves into the business aspects of the organization. Many of them move into roles like Managing Directors or Vice Presidents. In such roles, they oversee several divisions and business lines.
In these roles, Product Managers influence the product strategy and the marketing, sales, and finance functions in line with the company’s goals.
To know which role is right for you, understand what the day-to-day responsibilities of the roles look like:
Software Engineers and Product Managers drive the creation and evolution of software products. However, each has a distinct set of responsibilities, strategies, and perspectives. A project needs a blend of these roles and their unique skill sets.
When working as a software developer, it's important to acknowledge and appreciate each team member's unique roles and responsibilities. Even though everyone has specific tasks, teamwork is still crucial to success. That's where a Product Manager comes in - as a mediator between stakeholders and the engineering team, they gather feedback and ensure everyone is on the same page.
While the PM might help push specific deliverables, it's ultimately up to the engineering team to execute them. That being said, the PM might be held accountable for the project's overall outcome, especially regarding user satisfaction and management expectations. It's crucial to understand the difference between responsibility and accountability in any project and to work together to achieve success.
Software Engineers and Product Managers have contrasting approaches to tackling gaps in products. While engineers focus on technical obstacles and evaluating technologies, Product Managers prioritize bridging gaps and identifying opportunities. They streamline user scenarios, engage with users, and ensure alignment with key stakeholders. Collaboration between the two roles leads to impressive outcomes, with PMs providing valuable input and engineers making technical trade-offs to create optimized features.
The roles of software engineers and product managers differ significantly, not only in their skills and responsibilities but also in their approach to problem-solving. Software engineers are primarily oriented toward engineering and coding solutions, often diving deep into technical specifics and leveraging their expertise to overcome technical hurdles. Their analytical mindset drives them to focus on the intricacies of technology and the detailed execution of code.
Conversely, product managers are more collaborative and strategic, requiring a holistic perspective on solutions. They must understand the broader business goals and user needs, coordinating with various stakeholders to ensure that the product vision aligns with market demands and customer expectations. This overarching view helps them identify opportunities and streamline processes, ultimately fostering a product that meets both user and business needs.
Together, these roles create a dynamic synergy. Engineers apply their technical prowess to develop robust solutions, while product managers provide the strategic direction necessary for those solutions to thrive in the market. This harmonious collaboration ensures that both technical and product gaps are effectively addressed, leading to successful product development and innovation.
It is essential to recognize that different roles in product management have varying timeframes. Software Engineers (SWEs) typically operate on regular sprints, often on a weekly or bi-weekly basis, which enables them to structure their working schedules and remain on top of their tasks. In contrast, Product Managers (PMs) have more flexible timelines, as their responsibility lies in steering long-term strategies.
While PMs must pay attention to immediate tasks and customer feedback, they must also align with engineering sprints to provide the necessary specifications and artifacts. To be a good PM, it is essential to support the engineering team, and engineering timelines should influence their timeline but not necessarily be linked to them.
As a Software Engineer, it can be challenging to keep up with the frequent deliverables that come your way. From minor bug fixes to complex feature releases, each deliverable can impact the user differently. Some tasks, like maintenance tasks, may seem insignificant, while others can be game-changing for the product.
When it comes to customer-facing products, the release cadence may be less frequent, but the user impact of each new feature or improvement can be significant. It's essential to consider the user's perspective when prioritizing and planning deliverables to ensure a positive experience.
Software Engineers typically have a one-month ramp-up period before their responsibilities increase. At the same time, project managers may require up to two years, especially in larger companies. This is due to the complex decision-making involved in project management and the need for a deep understanding of the context. Although Software Engineers and project managers can impact user experiences, project managers are generally responsible for end-to-end user scenarios.
Let's simplify each role to help you decide which suits you best.
Do you enjoy strategizing, collaborating, and connecting user needs with product plans? If so, Product Management might be your fit. As a Product Manager, you'll shape the "what" and "why" of a product, drawing insights from user research. You'll understand customer desires, align business goals, and guide teams, from concept to product launch. If you love crafting solutions and teamwork, this could be your calling.
Are you intrigued by coding, solving problems, and building software solutions in a technical role? Software Engineering might be your compass. Software Engineers craft the "how" of products by turning ideas into functional code through their expertise in software development. If you thrive on coding challenges, value technical expertise, and want to create digital innovations, this path could be for you.
Remember, these paths often blend, and you're in control. Consider your strengths. Do you want to explore code and technology? Software Engineering might be your choice. Or do strategic thinking and teamwork drive you? Product Management could resonate.
Both roles demand learning and adaptability, shaping our tech world. As you gain clarity, let your choice align with your ambitions, guiding you toward a fulfilling career in the ever-changing tech landscape.
If you are passionate about technology, product management, and engineering are fascinating fields. They provide unique paths to explore, each with its challenges and rewards.
Whether you thrive on navigating the strategic landscape of product development or find joy in the creative process of coding, your choice of focus reflects your aspirations and strengths. By embracing the path that resonates with you the most, you can build a fulfilling and impactful career in this exciting industry.
Code rot is a common problem among engineering teams. It can compound unless it is well-managed.
Just like how we need to nurture our plants to grow or else they will be withered. The same should be done with code, otherwise, it will rot.
So, let’s delve deeper into the concept of Code rot, ways to recognize it, and how to address it.
Also known as software rot or software decay, It refers to the deterioration in the performance of a piece of code. It doesn't mean code doesn't break down or rot away. Rather, the quality of the code starts degrading over time, emphasizing the importance of clean code practices.
This further makes the software faulty, unusable, or need upgradation. If not taken care of in the long run, it can also directly impact the team’s productivity and morale.
Active rot shows signs of code while they are actively handled and maintained. Also known as Gradual Decay, these codes slowly worsen in small details. The common type of code rot can be found in every code base to a varying degree. This is because most software requires constant updates and bug fixing. Hence, deviating the program from its original design.
Dormant rot is easy to detect. This code isn’t being touched constantly which makes them useless as the rest of the application upgrades. The reasons could vary. A few of them include API no longer working, Hardware and platforms have stopped working, and missing device adaptations.
In this case, the code breaks in many places whenever a change is made. The code isn’t stable as software becomes difficult to maintain. When the code is fragile, every new change introduces several new defects. Even when the areas aren’t related to each other. They can be either detected early by an automated testing suite or found in production by end-users.
Declining software metrics don't always indicate code rot, but they can be a warning sign that the code needs to be reviewed. Sometimes, it's a slow deterioration, showing that the code isn't as healthy as it once was, and action should be taken to resolve it. A few of the metrics that can collect software codebase health data include Coupling, Cyclomatic Complexity, and Test Coverage. These metrics provide valuable insights into software complexity and can guide improvements.
When the code is hard to change, it can be a warning sign of code rot. Even when it is a simple change, it takes longer than expected. Moreover, one change may lead to other changes as well. The code becomes less adaptable to changes and prone to errors, instability, and crashes. As a result, this leads to a slowing down of the development process.
In continuation of the above point, code rigidity can also increase the time to deliver value. As the code is in an unhealthy state, more time will be needed to add new features. Hence, it takes longer to ship new features to the customers. Moreover, the developers may fear managing non-critical issues as they aren’t sure of the full impact of the change.
When the documentation isn’t updated or maintained for a long time, it gets out of sync with the code. This makes it misleading. As a result, it creates confusion and errors for developers to rely on it. If the documentation remains outdated for a long time, it can make the end users unhappy with the product.
You can start by defining what Healthy software stands for in your organization. Establish a set of common coding guidelines and practices for your team members. It allows them to be on the same page and move in the same direction. Moreover, it creates a social contract between the team and lets them consistently write code.
Software metrics may not necessarily identify code rot. But it can help in knowing the quality and health of the codebase. Various metrics such as cycle time, code churn, and cyclomatic complexity let the developers know how the code is performing. It can identify code smells and technical debt, track their changes over time, and much more. Hence, helping in further inspection.
Software metrics can also help in knowing the blind spots within your software development. Hence, it helps developers to know which areas need refactoring to enhance the overall quality of the code. Refactoring them in small, frequent iterations lets the code adapt better to new environments and improves its quality and longevity. This approach also assists in the gradual improvement of the code base and keeps it manageable, ensuring that your test suite remains effective.
While manual testing may take a lot of time, you can go for automated testing of the code. However, ensure that the code is written with testing in mind. It lets you know whether the code is working as expected. Moreover, if any recent changes are made, automated testing lets the developers know any previously working functionality has been affected. Hence, helping in detecting the issues early.
Lastly, after hiring the right set of developers, ensure that you train them regarding coding guidelines. Make them understand how refactoring should be done often and coding best practices. Try aligning them with other developers. Create a culture of continuous learning and foster open communication in your organization.
While code rot is a universal problem, It can still be prevented. Take care of your code base often. If any issue is detected, take the necessary steps at the earliest.
Typo, an intelligent engineering platform, can help in identifying SDLC metrics. It can further help in detecting blind spots and reducing code rot.
Speed is crucial in software development, but it’s not the only thing that counts. Without clear direction and purpose, your team may struggle to stay on track and deliver valuable results. This is where scrum velocity can help you.
So, let’s delve into the concept of Scrum velocity, how it’s calculated, and why it’s a game-changer for Agile teams.
Velocity is speed with direction, and development speed without direction is an utter waste of time. Therefore, team velocity in scrum development is the team’s capacity for producing useful, working software. Simply put, scrum velocity is one of the key agile metrics that represents the capacity of a development team to achieve a given purpose.
For example, if a team completes user stories with a total of 30 story points within a two-week sprint, their velocity for that sprint is 30.
To calculate velocity in Scrum, follow these key steps. First, determine the unit of measurement to track progress and select a time frame (iteration or sprint) for the calculation. Once these basics are in place, track completed story points.
Story points are used in Scrum to estimate the size or complexity of user stories or backlog items. Teams can compare and prioritize different pieces of work based on their difficulty level.
Track progress during the sprint by recording the total number of story points completed. This allows accurate calculation of velocity at the end of the sprint.
Velocity is measured per sprint and used for planning and productivity measurement. Tracking velocity, a fundamental Scrum metric, helps forecast how much work can be accomplished in future sprints and informs release and iteration planning. If there is a user story with 4 story points and another with 5 story points, then this sprint’s scrum velocity is 9 (4+5) by adding both story points.
Velocity tracking is one of the key agile metrics used in Scrum and other agile frameworks. Below are a few benefits of velocity tracking:
Monitoring velocity is essential for boosting team productivity and improving forecasting and planning. By tracking velocity across various sprints, the team can establish a standard and use it to estimate the amount of work they can handle in future sprints. This ensures that they can set practical goals and make informed commitments to stakeholders.
By using velocity tracking, the team can detect patterns and trends in their performance. They can also examine the factors that cause fluctuations in velocity, such as changes in team structure, task complexity, or external dependencies. Through iterative development, the team incorporates lessons learned from each sprint into the next, fostering a cycle of continuous improvement. By better understanding these factors, the team can refine and improve their procedures, resulting in more dependable and consistent delivery.
When teams can track their velocity and see improvements or consistency, it significantly impacts their motivation and overall satisfaction with their job. This can also foster a spirit of collaboration and transparency within the team as they work together to achieve their goals and continuously improve their velocity.
Monitoring velocity provides an exact measure for stakeholders and management to track team progress, capacity, and abilities. It encourages transparency and fosters trust between the team and stakeholders, leading to successful collaboration.
While velocity is a valuable metric for scrum teams, setting it as a target can create undue pressure and even lead to punishment for team members who fall short. A more compassionate approach focuses on tracking metrics and identifying any underlying causes of issues. This way, your team can improve their processes, eliminate bottlenecks, and incorporate new tools to enhance their skills over time.
It’s understandable that teams approach projects in their unique way, so it’s not always fair or practical to judge them solely based on their speed. A team’s velocity can be influenced by various factors, including the project’s complexity and the team members’ individual skill sets.When calculating scrum velocity, it’s important to remember that story point estimates can be subjective. Comparing teams solely based on velocity can lead to a negative work environment, internal conflicts, and low morale. It’s better to use this measure to navigate situations within a team rather than to compare teams against each other.
When you introduce the concept to the team, it’s understandable that every team needs time to work together effectively. Whether they’re a new or old scrum team, they would take time to understand new complexities and create action plans. It’s unrealistic to expect them to perform at maximum velocity right away, and it’s common for leaders to have unrealistic expectations based on an outsider’s perspective. Only the scrum teams and managers working on the project can accurately estimate true scrum velocity, as they’re facing internal roadblocks and several complexities.Therefore, providing them with space and time to work together effectively is crucial. Business leaders who fail to acknowledge this may unknowingly hinder their team’s progress and prevent them from moving in the right direction.
Scrum teams must allocate time for unforeseen activities, such as addressing technical debt and critical bugs reported by customers. But teams who only focus on scrum velocity need more investment in quality.
Neglecting these essential tasks can lead to a decrease in the quality of the final product and cause issues for future timelines. Short-term focus on velocity can hurt progress and ultimately harm business success. Therefore, it’s crucial to invest in the necessary resources for scrum teams to work effectively and prioritize quality over speed.
While some team leaders rely on scrum velocity for project completion estimates, this may not align with Agile principles. Factors such as changing requirements, short development sprints, and unpredictable variables affect velocity.
Therefore, depending solely on a static tool or metric for progress measurement may not be an efficient choice, especially if it only provides an estimation instead of a precise timeline. It’s important to remember that scrum velocity can only offer an approximate timeframe for project execution and should be treated as such.
Overemphasizing scrum velocity as a performance metric can lead to inaccurate predictions and frustration when tasks take longer than expected.
Moreover, assigning blame for incomplete stories can create negative feelings among team members. To avoid these issues, remember that velocity should only be used for prediction purposes and not for comparison or competition. Ultimately, the goal of development should be predictable progress rather than constantly increasing speed.
While velocity provides a general sense of how much work has been completed, it doesn’t give the full picture. You must account for factors like technical debt, bug fixes, and non-functional requirements to ensure you get all the important details that impact the overall value the team delivers. It’s essential to look beyond the surface level and consider the specifics of what was achieved and the quality of the work.
As part of sprint planning, the Scrum Master plays a crucial role in facilitating these retrospectives and ensuring that the team's feedback is incorporated into future sprints.
As an Agile team, it’s essential to recognize the significant role that velocity plays in your success. By understanding your team’s past velocity, you can better plan for future sprints and set realistic goals everyone can commit to within the Scrum framework. This helps keep everyone on the same page and provides a clear measure of your productivity and progress over time.
It also enables you to make data-driven decisions and aim for constant improvement. Ensure you look at scrum velocity objectively and not as a sole indicator of performance and productivity.
By following some simple tweaks to your process and journey with scrum velocity, you can achieve your goals efficiently.
Developers are constantly juggling between one or the other tasks. It may seem a ‘normal’ thing, but it can harm the software development process. If not measured timely and properly.
There are many metrics that engineering managers can take note of. But, here we will be discussing one of the important yet overlooked metrics in software development – Code Churn.
In this blog, let’s dive deeper into code churn, what causes high code churn, and how you can prevent it:
Also known as code rework. It is when a developer makes changes to a specific piece of code including a file, a class, or a function during the development process. Although, it is a normal thing, but also depends on when and why it is taking place.By this, we mean that testing, reworking, and exploring various solutions to a problem is fine. Especially, during the beginning of the project when code doesn’t have a clear solution.
It is healthy and expected unless it surpasses 20% – This is when it is a problem. The lower the code churn, the closer you get to a release date.
Common workflows and dynamics that can result in a high churn rate include:
Prototyping is a natural and healthy trend. It is usually seen when there is a new or unfamiliar project. During these times, the churn rate may rise to 60-80% and this is not unusual.
Apart from prototyping, redesign, and POCs are all examples of where large chunks of code are rewritten. Hence, it is fine to allow developers the time and space to research and experiment.
But, if it continues for an extended period beyond what was expected then it is a cause for concern. It could be that the developer is not able to comprehend the specific components or the entire problem. Or the problem could be complex.
One of the main factors behind high churn rates is inconsistent or unclear requirements. It further spreads to subsequent phases of software development which compromises the quality of final products.
It could also be that the requirements change midway through the work which is another reason for high code churn. Due to this, developers may rely on their best guess to interpret and fill in any gaps. As a result, some assumptions could be wrong too.
This further damages the morale and progress of the development team.
Uncertain developers may also impact team performance as they juggle between various approaches, such as:
Any of the above leads to subsequent changes in the code base which results in a delay in progress. Since decisions are constantly revisited or revised.
Complex tasks are another reason for higher code churn. Since the developers are continuously exploring and backtracking the project, it is not unusual that churn rates may exceed the desired level.
But, as mentioned above, if it goes on for too long, then it is a cause for concern. It could be that developers may not have the resources they need or may require additional help.
It can also increase Technical Debt resulting in high code churn. Developers take shortcuts and make compromises that hinder the entire development process.
Software developers are more likely to be burnout due to their busy work schedules. Even when enough resources are available and they have the required skills, developers who are burnout may not be able to do their tasks efficiently.
It can further result in becoming disinterested in work, failing to show up, and increasing the rate of presenteeism. Hence, developers may want to change their jobs resulting in an increased turnover rate.
When former developers resign, new ones replace them. They would need time to familiarise themselves with the existing code and team. Hence, it leads to knowledge loss which causes potential errors or inefficient changes.
Minimizing and managing code churn is done by measuring it. This allows you to prepare to take things in control when there is an increase in code churn.
Measuring it helps you understand the software development process and know how many times code is changed. It also lets you see in-depth insights into internal and external hurdles allowing you to create actionable plans.
It is the measure of the number of times the developers made changes to the file in GIT control.
The number of lines of code that were added to files for the code that was written recently.
The measure of lines of code that was deleted from files within three weeks of writing the code.
The measure of lines of code that was modified within three weeks of writing the code.
The total of lines added, lines deleted and lines modified.
High code churn usually arises when requirements are not properly defined. Hence, it is important to take sufficient time to understand the requirements.
In case, the requirements are ambiguous, ask for additional clarification and review it once before starting with the project. Make sure that every team member is on the same page and knows what needs to be done.
Also, aware clients and stakeholders as well of how mid-stream changes can result in slow delivery and increased time.
Higher code churn usually occurs due to ineffective planning. Always use data-driven and factual insights to plan team and task allocation for reducing code churn. It includes thorough pre-development preparation, comprehensive requirement analysis, and careful project scheduling. This reduces the likelihood of frequent code changes or major rework during later stages.
Moreover, effective planning allows software engineering teams to navigate new areas of the codebase.
Understanding the root cause lets you identify a long-term solution that helps in improving the quality of the database.
For example, if you are aware that the developers are still lacking needed skills, you can involve pair programming sessions with senior engineers.
Failing to address the root cause makes you constantly make changes to the codebase which lets you create a cycle of rework and inefficiency, potentially leading to bug fixes and future quality problems.
Usually, developers spend more time reading code than writing it. Hence, ensure that the code is readable to all.
It could be that developers may have different professional qualifications and work experience. Their language preference and writing styles could be different from each other. Hence, implement standardization in the workplace. And ensure that your team knows about it.
Also, select coding style guides. It will allow developers to read code easier and faster. It further helps in promoting best practices and coding techniques, leading to low code churn.
The code review process lets developers catch errors early in the development process. This further helps in improving code quality.
Apart from this, code reviews also allow team members to identify areas where code needs refactoring. As a result, helping them to prevent the need for extensive rework later. Code reviews let developers get honest feedback at the right time.
Typo’s automated code review tool identifies issues in your code and auto-fixes them before you merge to master. This means less time reviewing and more time for important tasks. It keeps your code error-free, making the whole process faster and smoother.
High churn can signify that developers are innovative and determined. But, when it goes on for a long period, there is a problem that needs to be addressed as soon as possible.
Pull requests are made on Git to work with a team collaboratively. In most open source projects, the contributors request the review and acceptance of a branch, and then depending on the vitality of the code, it is either accepted into the code or not.
A pull request serves as a crucial mechanism for contributors who wish to offer code enhancements to a project. It is a process where the project's maintainer is asked to review and potentially merge the contributions into the mainline branch.
While pull requests are a staple of collaborative coding, it's important to note that they are not a native feature of Git itself. Instead, they are a key function provided by source code management (SCM) platforms. GitHub was instrumental in popularizing pull requests, and today, they are a common feature across platforms like GitLab, BitBucket, and Azure DevOps.
Quick note: Though Git does offer a command called request-pull, this predates hosting services such as GitHub. It generates a list of changes in the format of a patch file, which is then typically sent by email. This nod to Git's history highlights the evolution of collaborative coding practices.
However, what happens when it is not merged and needs to be reverted? This is why we’ll tell you how to revert a git pull request.
You want to avoid being in a position of reverting the pull request as often as possible, but sometimes, you just have to do it. And a lot of situations are beyond your control. So here are some of the reasons:
There are multiple ways you can revert a git pull request; some are safer than others. Here are some of the methods:
Reverting a pull request in GitHub is a straightforward process that allows you to undo changes from a previous merge. Whenever a revert is made, it creates one revert of the merge commit. If you have write permissions, go ahead with the following steps:
This thorough approach ensures that any unwanted changes from a previously merged pull request are efficiently reverted, maintaining the integrity of your project's codebase.
The Git revert command helps you create an inverse to the introduced changes and adds a new commit with these changes. This method is non-destructive, meaning it preserves the history of the repository while effectively negating the changes made by the pull request.
Here are the steps:
This step doesn’t remove the changes made but adds changes to negate the pull request. If the merge was done using methods like squash or merge commit, you can target the resulting merge commit directly. However, if rebase was used, you’ll need to reverse each individual commit.
The previous method altered the new reality caused by the merged unneeded pull request, but Git reset is like going back in time to change what was done.
While this might have unintended consequences, it might still be a route you can take if needed, and here is how you can do it.
It's crucial to understand the risks associated with this operation. Rewriting history, especially on the default branch, can lead to significant issues. You may disrupt the historical integrity of the codebase, making it difficult for anyone, including your coworkers, to trace how the code has evolved over time. This can impact collaboration negatively, as the shared understanding of the project's development might be lost.
Moreover, performing a hard reset can lead to the permanent loss of commits. This means you might lose valuable work and insights into the development process—something that cannot be undone. Be sure to thoroughly consider these potential consequences before proceeding, as the operation is not without its drawbacks.
Understanding how pull requests (PRs) operate on different source code management platforms—such as GitHub, GitLab, Bitbucket, and Azure DevOps—can significantly impact a team's workflow and efficiency. Each platform offers a unique experience when it comes to handling pull requests, though they all aim to facilitate collaborative coding.
Reverting a pull request in GitLab requires understanding the platform's nuances. Unlike GitHub, which allows you to easily revert any pull request regardless of how it was merged, GitLab has specific criteria. In GitLab, the Revert option is available primarily for projects using git merge to accept merge requests. This method results in a "merge commit," which GitLab can revert.
By following these steps, you can efficiently manage pull requests in GitLab while recognizing the limitations and capabilities specific to its platform.
The pull request (PR) process significantly influences the timeline of software development, often contributing to unexpected delays. One of the primary reasons for these delays is the idle time during code reviews. On average, code reviews can remain unaddressed for a substantial portion of the development cycle, which elongates the overall process.
This phase is commonly the most time-consuming aspect of development. Companies prioritize metrics like PR merge time because unresolved code reviews can lead to merging conflicts. When a PR is not reviewed promptly, it heightens the risk of conflicts that require additional time to resolve.
Improving the pull request pickup time can markedly enhance efficiency. Early attention to PRs reduces waiting periods, streamlining the process. Moreover, PR size plays a crucial role. Smaller PRs are typically easier and faster to review, which results in quicker merges and fewer issues.
In summary, by optimizing these PR-related metrics, teams can significantly reduce cycle times and improve overall productivity in software development.
While the core workflow of branching, making changes, and merging remains consistent, differences lie in integration capabilities, user interface, and review processes:
In conclusion, while the fundamental concept of pull requests remains consistent, the nuances across platforms can greatly affect how teams collaborate and manage code. Understanding these differences can help organizations choose the best tool for their development needs.
Pull requests are an integral part of working collaboratively, and merging them by mistake or without enough review can cause many issues to the codebase. Then reverting this process can have other consequences you want to avoid. Therefore, have an internal process to merge pull requests. Ensure everybody is on board with the code reviews needed for the process and a checklist to denote when a merge is acceptable.
To further avoid the need for reverting pull requests, consider implementing a more structured approach:
Reverting pull requests should be an exception, not the norm. If it becomes common, it may indicate deeper problems within the team. Addressing these core issues can lead to a more stable development cycle.
Improve your engineering metrics, such as the time it takes for a pull request to be picked up and reviewed. Long review times can lead to conflicts and delays, so work on reducing these durations.
By adopting these practices, you can significantly enhance your code review process and minimize the need to undo pull requests, fostering a more efficient and reliable workflow.
Counting lines of code can be used as one of the metrics to assess your developers' productivity and the efficiency of code bases. Therefore, in this blog, we dive into the different methods to count lines of code and what we think about this metric.Let’s dive in!
There are several ways to count LOC, some more efficient than others with different objectives. So we have a list for you to use the best method that suits your needs.
Counting lines of code manually involves going through each line of code and tallying the lines while excluding comments, blank spaces, and non-executable lines.To do this, open the source code file and count the lines with a paper or text editor. Go through it line by line and check for executable code.Once you are done, note the total count.However this method might sound simple, yet it is tedious and prone to errors. Automated tools are more accurate and efficient, and we will discuss them in the following methods.
The Count Lines of Code (CLOC) command is a tool that automates counting lines of code.Here's how to use the CLOC command:
Here is an example of the tool and its results.
The automated categorization of lines into different types and comprehensive statistics using CLOC makes it superior to manual counting. You can trust the reliability and efficiency of this tool to save you a lot of time and effort.
Here is an example of the tool and its results. CLOC offers outputs in various formats, ensuring you can extract data in nearly any text format you need. This flexibility makes it an excellent choice for teams needing detailed insights across diverse file types.
For those using integrated development environments, consider VS Code's extension that offers a user-friendly approach. The VS Code Counter extension can be installed directly into your IDE. It provides real-time tracking of lines of code in your current file and across entire workspaces. Moreover, it allows teams to customize how it interprets each tracked language using a file, without requiring complex terminal commands.
By leveraging these tools, teams can efficiently monitor their codebases, making these solutions invaluable for developers aiming to maintain clean and well-documented projects.
While the above methods show the lines of code, if your code increases in more blanks, comments, and statements, then the number gets inflated without any value added to the functionality.Therefore, statements count is much more helpful in understanding the executability and functional efficiency of the code.In languages like C, C++, C#, or Java, a statement ends with a semicolon (;). And in languages like basic and VB, several statements can be added with a colon (:). Thus, the way it is done differs, but the logic remains the same.The executability (XQT) is calculated by dividing the number of executable statements (STMTX) by all the statements (SMT).Here are some specifics of this method:
While this does provide code complexity information, it still needs to be a fool-proof method. Factors such as data dependency and error handling can hamper the executability of the code.
When measuring developer productivity, it's crucial to select the appropriate metrics. Simply counting lines of code may not be dependable. Instead, experts advise measuring the number of executable statements within the runtime environment, which is a more comprehensive and precise comprehension of progress.Here are the steps:
Following these simplified steps, you can easily count the lines of IL code in your program.
When evaluating your codebase, understanding the difference between various lines of code metrics is crucial. Let's explore the distinctions between raw lines of code, source lines of code (SLOC), and logical lines of code.
Raw lines of code are the simplest form of counting. This metric includes every single line in your code file—comments, empty lines, and all. While it may not offer the finest granularity, it serves as a quick snapshot showing the size or scale of a given code segment. For instance, if a branch in your repository suddenly swells to thousands of lines, it might be a signal to review and possibly refactor to maintain code quality.
Source lines of code take a more refined approach by filtering out non-essential lines such as comments and blank spaces. This metric aims to capture the "active" lines in a codebase—those that are truly part of the executable logic. SLOC counts only the lines that contribute directly to the functionality, offering insights into the real complexity of a project. For example, consider a loop in JavaScript:
for(let i=0; i<10; i++) {
console.log(i);
}
Here, the curly braces and other syntactic elements take up space but offer no added functionality, which SLOC doesn't account for, giving a clearer picture of functional length.
Logical lines of code delve even deeper by counting statements instead of relying on physical line breaks. This measure accounts for the number of logical endpoints in code, often identified by semicolons in languages like Java or C++. Logical lines adapt to languages that lack rigid syntax for line endings, like Python, where line breaks are not necessarily indicative of new logic. Thus, it's a more universal and accurate reflection of code complexity across different programming paradigms.
Each type of code line metric offers unique insights into a codebase's complexity and productivity. Depending on the programming languages in use and the team's goals, understanding and applying the right metric can improve code management and development efficiency.
In summary, knowing the distinctions between these metrics allows development teams to make informed decisions about code maintenance, refactoring, and optimizing code review processes.
Counting lines of code has been a long-time metric; however, every tool and method gives different answers.Using it as a tool for productivity can be problematic because it is not comparable or fair unless you compare the same team’s code within the same team for the same code, language, and style. Here are some more points for you to consider:
While it's tempting to use LOC as a straightforward measure of productivity, this approach is riddled with misconceptions:
In summary, while LOC can provide some insight into the coding process, it should not be the sole metric for evaluating developer performance. Emphasizing quality, collaboration, and the broader context of work is crucial to fostering a productive and positive development environment.
Relying solely on lines of code as a productivity metric can be misleading. While it may offer some insight into a software development process, it fails to capture the full picture of what your organization is achieving. Here’s how you can balance this metric with other key measures to get an accurate view of your team’s performance.
Counting lines of code offers a quantitative look at productivity, but it doesn't account for the quality of the output, problem-solving efficiency, or impact on the organization. Overemphasizing this metric could steer your focus away from meaningful achievements and place undue pressure on your team, possibly sinking the entire operation.
For a more thorough assessment, integrate lines of code with other engineering metrics. Consider incorporating:
By assembling data from various metrics, you can pinpoint areas that need improvement and develop actionable goals. This approach encourages the team to focus on enhancing both the speed and quality of their deliverables. Tools like Trello or Asana can aid in visualizing task progress and identifying obstacles.
Shift the focus from sheer volume to strategic impact. Metrics like user engagement and customer satisfaction levels can better reflect the success of your product, aligning technical achievements with business objectives.
In summary, while lines of code can be a useful starting point, it's critical to balance it with a range of other productivity and quality measures. Doing so ensures that your organization remains agile, efficient, and focused on its broader goals.
LOC can give you glimpses into code complexity, code length, and executability, but that’s where its importance should stop. Typo’s CEO and Founder, Kshitij Mohan, says, “Measuring developer productivity solely by lines of code is like assessing a painting by its brushstrokes. It focuses on solution complexity rather than the complexity of the problem at hand. And like most metrics, it means very little without context.” Therefore, we believe you can count the lines of code all you want, but don’t use it as a metric to determine which code is better or which developer is more productive. Use it as intended – as a metric to help you along the way.
Moving to a different role in your career is always exciting, but that doesn’t mean you can’t also have some self-doubt and anxiety. As a programmer, your responsibilities are more focused on your deliverables and some amount of collaboration with your team member. However, as a manager, your duties will look different.
Therefore, in this blog, we break down some tips to make the transition from a developer to a manager smooth for you.
Moving from being a programmer to a manager can seem daunting, but it's not necessarily a one-way street. With the right approach, you can transition safely using a trial period, and this allows you and your manager to assess if the new role suits you.
It's also beneficial to develop your soft skills during this time by mentoring a junior employee. This is an excellent opportunity to experience management and take responsibility for someone's career growth.
Working closely with your mentee enables you to evaluate your suitability for a management role without formal commitment. If your mentee responds positively to your mentorship style, it can be a strong sign that management is a good fit for you. Remember, this is a journey, and it's okay to take your time to determine if this is the right path for you.
As someone who understands the ins and outs of software development, you know that producing quality code and delivering outstanding products requires the collective efforts of your team.
As a manager, your role is pivotal in ensuring that your team has all the resources needed to succeed. While hands-on work may still be necessary, a significant part of your job involves managing people and projects. This could mean supporting team members who may be going through a tough time or encouraging someone contemplating leaving to stay.
It's a challenging experience that requires emotional investment, but it's crucial to remember that your efforts play a significant role in keeping your team happy and productive. Remember, as a manager, you're not just overseeing a team but also responsible for their well-being and success.
In today's hybrid or remote work environment, your communication skills are more essential than ever, especially when it comes to writing. As a manager, you spend a significant amount of time typing away on your keyboard, exchanging and managing information. To sharpen your communication skills, it's essential to set clear, measurable goals around how you respond to emails and messages.
As a new manager, you'll quickly learn that a timely response is often more valuable than a delayed one that's been meticulously crafted. Finding the right balance between timely and thoughtful communication is critical to effective management.
Additionally, as a manager, you must be more empathetic in your communication. This skill isn’t merely about language; it’s also about the tone you use and the words you choose while communicating. It will allow your team to be more transparent with you and aid in a more cooperative team spirit.
As a manager, it can be a real challenge to balance your time between overseeing your team's work and getting your hands dirty with coding. While you have a range of important tasks to manage, such as setting project goals and managing resources, these duties can often limit the time you have available for coding, which can be frustrating.
In addition to these managerial tasks, you may also find yourself supporting and mentoring your team members, engaging in strategic planning activities, communicating and collaborating with stakeholders, and managing administrative tasks. All of these activities require your presence and engagement, which can further limit your time for coding.
It's important to remember that the amount of coding you do as a manager can vary depending on the size of your team, the nature of your projects, and the structure of your organization. In some cases, you may still have opportunities to contribute code on a limited basis, particularly in smaller teams or more hands-on managerial roles.
Even though you may code less as a manager, your technical expertise and understanding of the development process remain incredibly valuable in decision-making, architectural discussions, and providing technical guidance to your team. So, don't worry, you may not be coding as much as you used to, but your contributions are still significant and appreciated by your team.
Establishing trust within your team is crucial as a manager. It's essential to provide your team members with clear instructions and expectations while assigning tasks based on their skills and expertise.
Ensuring open communication is key, and creating a safe space where team members can speak freely without fear of judgment or backlash is essential. Because remember when you were a developer and maybe someone didn’t trust you enough or when you felt micromanaged? Yeah, you don’t want your team members to feel that way.
Giving them the freedom to make decisions and solve problems within their areas of responsibility is essential too. Also, don’t forget to celebrate their accomplishments, support professional development, and practice transparency are all vital components to building trust.
Remember that trust takes time to develop, so lead by example and show your team members that you trust their abilities and support their professional growth. With these efforts, you can create a positive and productive work environment for your team to thrive.
As a manager, managing your time effectively can be a challenging task. Unlike individual contributors, you may have limited time to focus on creative problem-solving. This means you must protect your team members' time by minimizing unnecessary meetings or interruptions. To ensure maximum productivity, many managers schedule all internal meetings on a specific day of the week. As a great manager, you can get into the "flow" state quickly. By working in shorter blocks of time, usually around 20 minutes, and focusing on one task at a time, you can achieve this. By switching between tasks without losing productivity, your team can benefit from a positive and productive work environment.
A new role can be daunting, but if that’s what you want, then it can also be an exhilarating experience. Remember always to keep learning and focus on your team; you will know how you are doing as a manager in how they collaborate with you and each other and how openly they communicate with you. It can be tricky initially, but by improving, you can surely be successful.
While thinking about how to be a better manager, you can also include tools that can help you and your team. A platform that allows engineering teams to maximize productivity and reduce stress will be a game changer for your new team. Typo can be your friend in this process; you can schedule a demo to learn how!
‘Product Hunt’— a popular destination for startups, early adopters, and investors. It is considered to be a go-to platform that turns your product into a business if done right.
Considering that, we launched ‘Typo’ on 22nd February 2023 on Product Hunt.
To our surprise, it exceeded our expectations and we became product #1 on launch day with ~2000 upvotes. But, that’s not all! We also became the #1 product of the week and #2 product of the month.
It not only gave us 300+ signups globally but our website traffic was also boosted by 8x.
In this article, we have shared our extensive learning that made our product a success. Hope it helps everyone who is planning to launch their product soon on a product hunt.
We are proud of how ‘Typo’ launch became a huge success. But, it wouldn’t have been possible without the Product Hunt platform. We prepared everything for our launch, the Product hunt gave us much-needed attention and visibility.
Before you start with the pre-launch preparation, know what your goal for your product is. I.e. Get clear on what outcome you want to achieve!
Our main aim was to find early adopters who can give us product feedback.
Following are the few objectives that you can choose from:
P.S: Choose the goal that will be beneficial for your product in the long run.
Now, as you are clear about your goal, you can start with pre-launch preparation.
We set aside 3-4 months for pre-launch time. We jot down the entire plan and created visuals and content. Everything was done during this time.
Ensure that the product is ready: Who would like to give the new users hard time while they test our product? Nobody, right?
The first thing we checked was that all the features in our product are working fine. We tested it constantly. Also, if there are any bugs, we ensure to fix them on a priority basis.
We also ensure that the website is appealing and has a smooth user interface. Our CTA needs to be visible. Also, everything about the software should already be on the website.
Makers need to be active in the product hunt: Makers = The ones who create the product and launch them on the product hunt.
Ensure that the makers are active and responsive prior 3 months before the launch. By this, we didn’t mean to keep promoting your product. But, you need to try out new products shared on the platform, share feedback and ask questions to the creators.
In short, you need to take part organically in the platform. Ensure that you are not active only for the sole purpose of launching your product. Be deeply involved in this platform.
For us, it has been the most important aspect of our launch time. Our makers were constantly engaging with other creators and sharing their feedback. And in the end, it was all worth it!
Decide the time and date beforehand: The product hunt homepage is set to 24 hours cycle. Hence, deciding the time and date is the crucial aspect of the launch day.
We decided to launch our product on 22nd February, Wednesday at 12:00 AM PST. Let us break it down for you to understand why we choose this particular day and timing.
As mentioned above, we aimed to acquire early adopters to get honest feedback. Tuesday, Wednesday, and Thursday are considered to be the perfect days for the same. Hence, Wednesday it was.
The product hunt homepage refreshes at 12 AM PST every day. So, we decided to make it live at this time. It will ensure that users will get enough time to review and experiment with our product.
Note that, posting after 9 AM PST is a big no-no.
Get your team on the same page: Product hunt launch is a team effort. Ask your team members to be actively engaging on this platform. Let them know how their efforts can contribute to the success of our product.
Make them understand what you are doing and assign the roles accordingly.
Example: Who will be in charge of content planning?
Who will be posting on social media channels?
(This particular part we will be covering in the next section)
We created a slack channel where we discussed everything regarding our product hunt launch. It allowed us to be aligned with everyone on our team. If there are any suggestions from their side, they can discuss them openly in that slack channel.
Have content strategy planned for the next few days: The content strategy plan is the most overlooked yet important part of the launch. Since, the next few days will be quite busy, prepare a content strategy 2 weeks before the launch. We did the same and then assigned roles to the different members of our team.
You need to prepare and post individual content on social media channels. It includes Reddit communities, Discord channels, Facebook and Telegram groups, and many more. Also, make sure that you are not spamming on any of these platforms. As it could harm the product even before its launch.
Create a coming soon page for your product: Schedule your launch on Product Hunt at least 10 days before. It further allows you to create a coming soon page for your product. After this, you can see the CTA of ‘Notify me’ on the page.
Anyone clicking on this will get a notification via email about the launch of your product. Try getting as many followers as you can get before the launch day. So, you are assured about the early upvotes on your product when launched.
Identify hunters of your product: Hunter: The early adopters of the product who can ‘hunt’ the product and show it to the rest of the community.
Having a hunter is not a necessity, but it can bring a lot to your table. Their followers also learn about your product, increasing engagement and visibility.
Kudos to Kevin William David, a well-known hunter who agreed to hunt us on a product hunt. This was another major factor in the success of our product.
If you are looking out for the hunter, check out their previous hunts and pitch your idea to them. You can reach out to them via email or Twitter. Try identifying your hunter at least 10 days before the launch. You can find the hunter for your upcoming launch here.
Besides this, self-hunted products can also be considered.
While major work is already done, here are a few other checklists that also need to be kept in mind.
Set the right positioning of the product: The description is the most important part of your Product Hunt launch. It should be specific and have a clear message about your product.
For the Typo page, we wrote a description that is to the point and short. We answered the two major questions:
Ensuring that it is well-optimized and connected to our unique value proposition. As it resulted in driving organic traffic to our product.
Decide visuals for the profile: Visuals attract a lot of attention. Create appealing images, GIFs, and launch videos to add to your product hunt profile. Make sure they are of high quality and clarity in messaging.
The visuals we created for our page have a minimal design yet clearly describe our product’s features. Our launch video includes all the important information about our product that helps users understand our product in-depth which further, assists their experience.
You can also add image/video screenshots to your page. Also note that, if you are using a GIF image as a thumbnail, it shouldn’t be flashy.
Add PH widget to your website: This will act as an indicator who still haven’t heard of the launch yet. And even for those, who want to learn more about the product.
Keep a check on website traffic: While you have already created a website, it’s important to keep a check on how much traffic it can bear. (Just in case your product goes viral!)
You can keep this day flexible. As the launch day could be your no-sleep day. (Since 24 hours are crucial for your product)
On this day, you can re-check if everything is on track for tomorrow. Don’t keep anything for the last moment.
This is like a 24-hour battle. Here, you are competing with various products that are launching on the same day. Make it worthwhile and for that, you need to be active throughout your day.
Involve every member of your team: Your team is your biggest supporter and cheerleader. Make them your brand evangelists so they promote the product in every way possible. But, also make sure they have explored the platform in advance. So, they know what and how it needs to be done.
You can also assign duties to them in advance so they don’t get lost at the last moment.
Also, don’t forget to let them know that they need to ask for support, not for upvotes. Since product hunt is strict about its guidelines and can report them as spam. (You don’t want to see any of your team members’ efforts go in vain.)
We are a team of 15 members and with our combined efforts, we became the #1 product of the day. If we as a small team, can do so, we assure you can give it a shot too. Trust us, size doesn’t matter. All it matters is your dedication and efforts.
Don’t reach out to your contacts all at once: This is a 24-hour activity. Don’t reach out to everyone altogether. You can divide your outreach into various parts.
For example:
And so on…
You can also ask a few of the team members to upvote early and some of them later. But, make sure that they are members for a decent period before the launch. Since creating new accounts for upvoting on the same day of the launch can again be considered spam.
No fake accounts as well! Since it can lower your upvotes or even avoid your product from being visible on the homepage.
To know your product and competitors’ performance on the product hunt, check out this link: https://pw2.akkio.com/ .
Create buzz on social media platforms: Just like how active you are on the product hunt, the same goes for social media platforms too. You need to let the people know that your product is now live.
A few of the social media channels that we used are:
We posted hourly updates on LinkedIn about how many upvotes we are getting. Either from our product’s page or a team member’s account.
We also posted BTS on our social channels. So that the audience can connect with us.
In Reddit and discord communities, we shared that our product is live. So, that they can support us and give us honest feedback.
In short, you need to make a lot of noise about your product on D-day. But, again make sure that you are not becoming spammy.
Be responsive on product hunt: Makers’ work doesn’t end with releasing their product. You need to respond to every comment and feedback on your product.
Keep interacting with them to learn how you can deliver them an even better experience. As engagement helps to bring visibility and recognition to your product.
Ensure that your answer are insightful & helpful for the users. Also, don’t forget to thank early adopters and hunters for trying out the products.
These responses and feedback can help in prioritizing your product roadmap. And can create a smooth user experience in the upcoming future.
Seek support from other tech startups: We work in a co-working space. Hence, we leveraged it to gain support from other tech startups working there where they shared their honest feedback and opinions about our product.
So if you are too working in a co-working space, it’s the sign.
Create a pre-launch and launch plan on google sheets: It’s not possible to remember everything regarding your product launch. Hence, it is advisable to prepare a detailed plan in advance on google sheets. (Or any other application that suits you well).
We created an in-depth plan that was shared with every team member. It made our product launch easier since everything was in one place.
Your product is now live. But, this is not over yet. You now need to ensure how much users are liking your product and what are the improvements to be done.
In other words, the Post-launch period is all about analyzing your product and making changes accordingly.
Thank everyone who support your launch: We became the #1 product of the day and our happiness seemed no bound. But, it wouldn’t have been possible without people who supported Typo.
The first thing we did after launch day was to express our gratitude to them. We let them know how much we appreciate their support.
And this isn’t about being the top product on the platform. Even if we haven’t been one of them, we still would thank them for their support. Since they took out their time to help us out.
Also, make sure that you personalized your message accordingly. You can also use social media channels to thank your supporters.
Analyze your launch: No matter how well we did on the launch day, the real game begins after it. We checked what really worked for us and what did not. We tracked our Product hunt statistics that includes upvotes, comments, and referrals. How many signups did we get and what do users usually expect from us? We did detailed analyses of our product on the platform.
Not to forget, we also keep a check on our website through google analytics too. We tracked website traffic during and after the product hunt launch, time on site, and bounce rate.
Since you are creating a product for the long run, analyzing every aspect of your product is crucial.
Track user usage: We prepared a questionnaire for tracking the beta users’ feedback. A few of the questions we include were:
We kept the questionnaire short and crisp. And so should you. We also tracked what features are users using, what they are finding difficult, and many more.
Ensure that you are transparent with the users about the tracking process. And also, you act on the insights as early as possible.
Keep promoting your product subtly: Social media channels are a great way to reach out to a wider audience. But, you don’t have to keep promoting your product directly always.
After the product went live, we shared the BTS of launch day – How fun yet challenging it was. We also posted a video thanking our supporters, creating memes around it, and so on.
We just make sure that we aren’t only asking people to try out our product. Rather, educating them, informing them about features, and so on.
We also started our blog section where we inform our target audience regarding engineering metrics, developers’ burnout, engineer managers, and so on.
Ask for support, not upvotes: Although, we have already mentioned it before. But, this is an important reminder for everyone launching on product hunt. Asking for upvotes can lead to more spamming that can trigger your algorithm. As a result, it can drop your product rank or remove it from the homepage entirely.
Ask for feedback, comments, and opinions, and help to spread the word. PH believes people should upvote and comment because they authentically like a product, not because they’re peer pressured into doing so.
New users shouldn’t sign in on launch day: New relevant users in your network should avoid signing in on the same day and upvote only on one product. Ensure that they are already active and engaging with other creators and communities.
Don’t spam on social media: Ensure that you are not spamming on your social media pages as well. This can come across as spammy or manipulation and hurt your product’s credibility.
Get everything planned: Don’t keep everything for the last moment. Jot down important tasks before launch. Also, even if you want to experiment, plan it before d-day.
Avoid bots for upvotes: Never use bots for upvotes. The product hunt platform will automatically remove them which can lower your upvotes.
Create an FAQ section to answer common questions: You can include common questions in the FAQ section. It includes features, pricing, availability, and many more. This will save the time of both makers and users.
If you didn’t become a product of the day, it doesn’t mean your product will not succeed.
Sharing the tips mentioned above may not guarantee you become #1 on the product hunt. It’s about how well you understand your product, audience, and insights.
Also, keep in mind that in the long run, your aim is to reach the target audience.
You can still share your product on social media channels and engage with the community.
Note that what worked out for us may not work for you. So, be flexible about the tips mentioned above and see what is right for you.
It may take a lot of time and effort, but it will be all worth it.
All the best! :)
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