What are the Different Types of Code Smells?

Megana Natarajan

Harold Abelson famously quoted, “Programs must be written for people to read, and only incidentally for machines to execute.”

Let us start with a software story: A development team once inherited a legacy system from a vendor some time ago. Everything seemed to function well on the surface. However, they were eventually forced to sift through endless 500-line methods, copy-and-paste functions, and confusing dependencies spread across dozens of files as soon as they tried to add basic functionality. What should have been an easy change became a terrible nightmare that lasted for over months.

Writing new features and maintaining and enhancing existing code are both vital aspects of software development. Even well-written programs can throw inefficiencies over time that make them more difficult to understand, maintain, or scale. These inefficiencies are often referred to as “code smells”, which are external signs of more serious problems with the system’s architecture. Similar to a bad odor in a room, code smells are indicative that something might fail if left unchecked, but they don’t always mean that something is broken at the very moment.

Why Understanding Code Smells is Important

Not all code smells lead to errors right away. Rather, it often increases technical debt, makes the codebase harder to maintain, and creates hurdles for forthcoming development. If ignored, these smells might lead to:

• Increased Cognitive Load: Smells like long methods or big classes make it difficult for developers to keep track of everything, which hinders the development and makes onboarding more difficult.
• Higher Defect Rates: Bugs are often hidden by smelly code. Duplicate code, for example, is when a defect is fixed in one location but left ignored in another. Shotgun surgery spreads edits over multiple files, making even minor adjustments dangerous.
• Growing Technical Debt: Smells accumulate “interest,” much like financial debt. When created on a disorganized foundation, each new functionality takes longer to implement, which results in inefficiency.
• Impact on Group Morale and Efficiency: Developers become annoyed by messy code, which results in time loss and burnout. On the other hand, codebases aid in faster delivery and boost confidence.
• Business Implications: Time to market and innovation are affected by unresolved code smells. Competitiveness is directly affected because teams spend more time untangling obsolete code than delivering new value.
• Importance of Early Awareness: While not every smell needs to be fixed immediately, detecting them helps teams set priorities. Awareness ensures the right balance between cleanup and progress.

Teams can reduce long-term expenses and improve code quality by identifying and fixing these smells early.

Types of Code Smells

Code smells are segregated into several general categories, i.e., Bloaters, Object-Orientation Abusers, Change Preventers, Dispensables, and Couplers. Let’s know more about them:

Code Bloaters

Bloaters occur when code gets too big or complex.

• Long Method: Techniques that are more than 50-100 lines long typically try to address several issues. Because developers have to set up a number of inputs and outputs, they become complex to test. Readability is instantly enhanced by refactoring into smaller methods with descriptive names.
• Large Class: A class tries to perform multiple tasks when it gathers an excessive number of fields or methods. This regularly hides redundant reasoning and transgresses the Single Responsibility Principle. Example: The division of duties into smaller classes (like OrderProcessor and InvoiceGenerator) makes responsibilities clearer.
• Long Parameter List: When a method receives six or seven arguments, developers are forced to remember the order and purpose of parameters. This finally results in errors. Usage is simplified by utilizing a builder pattern or parameter object.
• Primitive Obsession: It is where objects would have a better meaning, utilizing strings, integers, or Booleans instead. For example, defining a PhoneNumber class adds validation and self-documentation in place of passing a String for a phone number.
• Data Clumps: When sets of variables, such as street, city, state, and zip code, regularly occur together, they need to be treated as independent objects (Address). Clarity is enhanced and redundancy is brought down.

Object-Oriented Abusers

Misapplication of object-oriented design principles leads to these smells:

• Refused Bequest: When a subclass inherits methods it doesn’t utilize, it regularly signals that the hierarchy is not well-designed. A Square class that inherits from Rectangle but does not need all of its methods is one such instance.
• Switch Statements: Missing polymorphism is represented by long switch blocks that branch according to type codes or enums. For example, each subclass (Dog, Cat) should implement its own behavior in place of if(animal == DOG).
• Temporary Field: A field that is only used regularly clutters the classroom and confuses readers. It becomes clear when it’s actually needed when it’s encapsulated in a specialized class.
• Alternative Classes with Different Interfaces: It can be complicated for developers to switch or utilize two classes interchangeably when they have similar functions but different method names getName() vs fetchName()).

Change Preventers

These smells make code modification needlessly complicated.

• Divergent Change: When a single class experiences changes for unrelated reasons, like updating the database logic and user interface formatting within the same class. Ripple effects are reduced when responsibilities are divided.
• Parallel Inheritance Hierarchies: Developers are forced to mirror changes across hierarchies by utilizing parallel inheritance hierarchies (e.g., every new UI element needs a matching data class). This points to a design that is too rigid.
• Shotgun Surgery: A minor change, such as adding a field, needs changes in ten distinct files. Delivery is decelerated and regression bugs emerge more frequently as a result.

Dispensable Code Smells

Dispensables are components with little to no value addition.

• Duplicate Code: It is the largest maintenance killer. In the event that a bug is detected in one location, developers must recall to address it in each duplicate. This risk is prevented by extracting shared functions.
• Dead Code: Obsolete logic, unused variables, or outdated methods will exist in the codebase. New developers are confused by them and ask, “Is this still required?” Removing them helps maintain lean code.
• Lazy Classes: Classes that only wrap one or two methods with no actual values are called lazy classes. They utilize needless indirection.
• Comments: Although the documentation is clear, too many comments often hide illogical reasoning. Code should be rewritten if it needs paragraphs of explanation.
• Data Class: Feature envy is often encouraged elsewhere by classes that only contain fields and getters/setters and lack behavior. Coupling is reduced by assigning them responsibilities.
• Speculative Generality: “We might need this someday” mentality code adds unnecessary clutter. Adding functionalities when needed is beneficial to making future predictions.

Couplers: Unhealthy Dependencies

Problematic dependencies between modules or classes are the sources of these smells.

• Feature Envy: A method’s logic belongs somewhere else if it spends more time accessing another class’s fields than its own.
• Inappropriate Intimacy: When two classes have too much internal knowledge of one another, they form rigid dependencies that make it nearly impossible for them to adapt to changes on their own.
• Message Chains: Here is an example, the developer must call the customer.getAccount().getBalance().getCurrency() just to get information. This leads to exposing too many details.
• Middle Man: A class that exists only to pass requests elsewhere. Design is made simpler by removing the class.
• Incomplete Library Class: When programmers add hacks to library classes because the originals aren’t functional enough. This can be resolved with wrappers or adapters.

Common Code Smells in Practice

While the above list is exhaustive, some code smells are more common in real-world scenarios:

1. Long Method: They become “god functions” that handle several workflows, specifically in legacy code. Segregating them optimizes testing and modularity.
2. Large Class: Controllers or services regularly become bloated as a direct consequence of business logic creeping in. Dissecting them uncovers intent.
3. Duplicate Code: Identified when multiple programmers respond to the same issue in different sections of the application. Consistency is guaranteed by centralizing logic.
4. Feature Envy: Common in systems where data is stored in logic and models is stored in services. As a result, models finally convert it into “dumb bags of data,” and services grow unnecessarily complicated.
5. Dead Code: Developers often hesitate to eliminate code “just in case.” Unused code, however, decelerates understanding and confuses teammates. Version control ensures that deleted code can always be retrieved.

Taking shortcuts, adding “quick fixes” or failing to review code post deadlines are all instances of human practices that contribute to the increased incidents of smells. By focusing on these typical smells, code quality can be quickly enhanced.

The Impact of Code Smells on Software Development

Code smells can have serious impact if overlooked:

• Complexity Increases: Onboarding new developers takes more time.
• Refactoring Becomes Riskier: The code changes become even more difficult without impacting functionality.
• Defects Multiply: The likelihood of bugs rises with each change.
• Delayed Innovation: Teams spend more time solving issues rather than building new features.
• Maintainability: The cognitive load increases with each smell. More details need developers to pay attention to, which delays the development and increases onboarding costs.
• Defect Rates: Bugs are often caused by code smells. For example, inconsistent behavior may be introduced if duplicate code is fixed in one place but ignored in another.
• Technical Debt: Smells stand in for debt that needs to be paid back later, generally at a higher cost. Interest accumulates in the form of increased bug counts and delayed development, much like financial debt.
• Team Morale: Developers become tired of messy code, which can result in burnout or resistance to working on specific system elements.
• Business Impact: Time-to-market, client satisfaction, and even long-term competitiveness are directly affected by unresolved code smells for business.

Detecting and removing smells is an investment in your software’s long-term viability.

Refactoring to Eliminate Code Smells

Improving the internal code organization without changing its external behavior is called refactoring. General methods include:

• Extract Method: It breaks down complex techniques into smaller, more targeted ones. A billing process method, for example, can be divided into generateInvoice(), applyDiscounts(), and calculateTaxes().
• Inline Class: Removes unnecessary abstraction when a class has minimal responsibility.
• Introduce Parameter Object: Makes method calls easier by grouping related data into objects. You can use createUser(UserDetails) in place of createUser(name, email, phone, address).
• Move Method or Field: This reduces ‘Feature Envy’ by transferring logic to the class that owns the data.
• Encapsulate Field: To handle how public fields are accessed, getters and setters are utilized in their place.
• Replace Conditional with Polymorphism: Gets rid of lengthy if/else or switch blocks.

Refactoring makes code more resilient and flexible by systemically addressing code smells.

How Software Testing Helps Manage Code Smells

Testing and Refactoring go hand in hand:

• Regression Safety: Code may accidentally be broken during refactoring. Regression tests that are automated function as a safeguard to make sure that behavior hasn’t been modified.
• Developer Confidence: Developers are hesitant to clean code in the absence of tests. They are free to refactor when there is strong test coverage.
• Identifying Hidden Problems: Smells can often conceal more serious problems. Tests and refactoring unveil those hidden problems.
• Support for Continuous Delivery: Agile teams rely on regular changes. Code smells can be addressed without halting development due to automated testing.

For example, a group prevents redundant code from multiple modules. They run the risk of breaking functionality if they don’t have regression tests. However, they validate that the system continues to work properly following consolidation through test automation.

AI-Powered Testing and Code Smells

AI-powered test automation tools like testRigor can help with this. Although some code smells can be identified with the help of modern static analysis tools, software features after modifications are not ensured.

With testRigor, teams benefit from:

• AI-driven test automation that makes it easier to develop and manage tests using natural language.
• Strong regression coverage ensures that when code is refactored, functionality is maintained.
• Faster feedback loops during CI/CD help teams detect problems early.
• Confidence in refactoring is improved. With robust automated tests in place, developers can safely resolve code smells.

In essence, testRigor offers reliable automated validation to aid organizations in reducing the risks associated with resolving structural issues that code smells indicate.

Best Practices to Prevent Code Smells

Consider these procedures to keep your codebase healthy:

• Frequent Code Reviews: Encourage peer reviews to detect issues early.
• Automated Static Analysis: Includes instruments that detect usual smells.
• Refactor Constantly: Avoid waiting until the system goes out of control.
• Test Automation: For regression safety nets, utilize AI-powered tools like testRigor.
• CI/CD Integration: Utilize automated checks to detect issues before deployment.

Teams can consistently enhance their codebase by combining refactoring with thorough testing.

Conclusion

Code smells are warning indicators that shouldn’t be overlooked, even though they might not cause your software to fail immediately. Teams can proactively refactor and strengthen their systems by being aware of the different types of code smells.

Organizations can confidently address these smells with the aid of AI-powered test automation tools that ensure that functionality is maintained while the codebase gets cleaner, more robust and manageable.

Cleaner code doesn’t stop at making developers happy, it also makes businesses more agile, competitive and faster.