Understanding Code Smells and How to Avoid Them

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.

What is Code Smell?

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:

• Prevention of Design Decay: Regular refactoring helps avert the gradual deterioration of code design, keeping it robust and adaptable.
• Enhanced Readability and Maintenance: By cleaning up the code, developers ensure that it remains understandable and easier to maintain, reducing the likelihood of bugs.
• Timing for Refactoring: The ideal times for refactoring are before implementing major updates and after deployment to production. This ensures that the existing codebase is pristine before adding new features and allows for post-deployment cleanup.

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.

Top Code Smells and How to Avoid Them

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.

Duplicate Code

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.

• Identification: Look for identical or similar code segments, even subtle ones like repetitive structures or parallel inheritance hierarchies.
• Solutions:
  • When there is the same method, create the same Local Variable and reuse it; during the same class, create common Method refactoring.
  • Leverage the power of functions or loops to make code appear once in a program.
  • Use refactoring techniques such as the Extract method, pull-up method, and substitute algorithm.

Long Method

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.

• Identification: Notice when a function handles too many tasks or grows unwieldy in length.
• Solutions:
  • Establish maximum line counts for methods with your development team.
  • Use the ‘Extract method’ to break it up into several smaller methods, where each of them is doing one precise thing.
  • Remove local variables and parameters before extracting a method.

Dead Code

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.

• Identification: Use static analysis tools or modern IDEs to highlight unused code easily.
• Solutions:
  • Remove dead code completely after writing the code that replaces its functionality.
  • Use static analysis tools or IDEs such as Visual Studio to suggest removing unused code.
  • Refactor code to eliminate redundancies and maintain structure.

Lazy Class

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.

• Identification: Identify classes with minimal functionality or classes that have been left empty due to previous refactoring.
• Solutions:
  • Implement constant code reviews to identify and address lazy classes.
  • Determine whether the ‘Lazy class’ serves a legitimate purpose in the codebase. If not, remove it through the remove class technique.
  • Use the ‘Inline class technique’ to detect a lazy class and merge it with another class that uses it.

Middle Man

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.

• Identification: Discover classes that primarily pass requests to other classes without adding any processing.
• Solutions:
  • Document the reasons for removing the middle man to guide developers during code cleanup.
  • Use the ‘Move method’ when the method logically belongs to another class, improving cohesion.
  • Use the ‘Inline function’ when only a few class methods are not delegating and need to inline them into the caller.

Primitive Obsession

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.

• Identification: Look for excessive use of primitive types where small classes or objects should be used instead.
• Solutions:
  • Replace the data value with an object if the primitive fields logically belong together.
  • ‘Introduce a parameter object’ to represent the data and clean up the code base.
  • ‘Preserve the whole object’ when its state is needed together, avoiding extracting small parts of objects to pass around.

God Objects

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.

• Identification: Identify classes that seem to manage too many unrelated responsibilities or control too much of the system.
• Solutions:
  • Refactor the class into smaller, more manageable classes, each holding a single responsibility.
  • Apply design patterns such as Facade, mediator, or delegation to create clearer interaction between classes.
  • Structure code into independent, reusable modules.

Feature Envy

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.

• Identification: Notice methods that frequently interact with data from another class rather than their own.
• Solutions:
  • Look at the code and identify the class reference. Use the ‘Move method’ to consider moving relevant methods to those classes.
  • Use the ‘Extract method’ to move the part in question if only part of a method accesses the data of another object.
  • Apply design patterns such as strategy and visitor.

Large Class

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.

• Identification: Recognize classes with an overwhelming number of methods or responsibilities, making it hard to maintain.
• Solutions:
  • Keep the classes small and adhere to the single responsibility principle.
  • Use the ‘Move method’ to move a method or field to another class more closely related to it.
  • Ensure thorough testing before and after code refactoring to maintain the codebase.

Improper Names

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.

• Identification: Identify names that are either too cryptic or too verbose, making code comprehension difficult.
• Solutions:
  • Keep variable names short and descriptive, and function classes should include one verb describing what they do, without adding too many words.
  • Adopt consistent naming conventions among the development team.
  • Use code analysis tools to detect naming style violations and suggest improvements.

Comments

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.

• Identification: Notice excessive or outdated comments that could be replaced with clearer code.
• Solutions:
  • Use the extract function to explain what a block of code does.
  • Remove comments; rather, rely on clear and descriptive functions and variable names to convey the code’s purpose.
  • Explore pattern techniques or libraries that can enhance code clarity without relying on comments.

Long Parameter List

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.

• Identification: Identify methods with excessive parameters that complicate function use and increase error rates.
• Solutions:
  • By the ‘Introduce a parameter object’ method, create a new object from the list of parameters and transfer it as a single argument.
  • Use ‘Preserve whole object’ when the parameters belong to a single object.
  • Use ‘Replace parameter with method call’ when some of the arguments are just results of method calls of another object. This object can be placed in the field of its class or passed as a method parameter.

Shotgun Surgery

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.

• Identification: Detect scenarios where making a single change requires altering many small areas across the codebase.
• Solutions:
  • Document clearly how many files are used while making conceptually simple changes.
  • Refactor and adhere to the single responsibility principle by handling multiple concerns into smaller, focused components.
  • Reduce the tight coupling between classes either by applying the ‘Dependency injection’ technique or using design patterns like observer or strategy patterns.

Inappropriate Intimacy

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.

• Identification: Identify tightly coupled classes that interact too intimately, which could hinder future changes.
• Solutions:
  • Use the ‘Encapsulate field’ when inner data needs to be exposed instead of being private.
  • Use the ‘Extract interface technique’ to define a common interface for the classes that need to interact with each other.
  • When two classes are too related yet don’t talk much to each other, they need a split, merge, or refactor.

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.

What Are Data Clumps and How Can They Be Managed in a Codebase?

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

1. Extract Class:
   • If fields are often repeated across different classes, consider extracting these fields into a new class. By doing so, you transform the grouped information into its own object. This not only centralizes the data but also encapsulates behavior where it can be more effectively controlled.
2. Introduce Parameter Object:
   • When you see functions repeatedly using the same parameters, implementing a parameter object can clean up your function interfaces. This method involves bundling these related parameters into a single object, streamlining function calls and simplifying data handling.
3. Preserve Whole Object:
   • Another approach when dealing with repetitive functions is to pass an entire object as a parameter instead of individual pieces of data. This ensures that related data stays together in a cohesive manner, making your code more comprehensible and less prone to errors.

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.

Best Strategies to Prevent Code Smells in Development

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:

Embrace Regular Refactoring

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:

• Prevents design decay.
• Increases code readability and maintainability.
• Reduces bugs.

When to Refactor:

• Before introducing major updates.
• Post-deployment, to streamline your code for future work.

Tools to Consider:

• Typo
• SonarQube
• Visual Studio IntelliCode
• Rider
• Eclipse IDE

Implement Continuous Integration and Deployment

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:

• Facilitates fast feedback loops.
• Reduces manual errors.
• Enhances software quality.

By automating the build and testing processes, you ensure any potential smells are immediately flagged and addressed.

Utilize Automated Code Reviews

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:

• Fast identification of code issues.
• Consistent adherence to coding standards.
• Full visibility into the code’s lifecycle.

Popular Tools Include:

• Typo
• Eclipse
• Visual Studio
• CodePeer

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.

The Role of Continuous Integration in Reducing Code Smells

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.

Typo - Automated Code Review Tool

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:

• Supports top 15+ languages including C++ and C#

• Understands the context of the code and fixes issues accurately

• Optimizes code efficiently

• Standardizes code and reduces the risk of a security breach

• Provides automated debugging with detailed explanations

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