Code Smells

Code smells are pieces of code that might benefit from refactoring for better readability, security, and performance of the whole application. There are tons of different code smells, we try to focus on the most important to us:

A code smell is also described as any character in the source code of a program that possibly indicates a deeper problem.

Why Code Smells are Important

Code smells are essential to consider because they can have various negative consequences on software development and maintenance, including:

Reduced readability and maintainability: Code smells can make code harder to read and understand, increasing the likelihood of introducing bugs during maintenance or updates.
Increased technical debt: Ignoring code smells can accumulate technical debt, which can become expensive and time-consuming to pay off over time.
Hindered collaboration: Complex or smelly code can hinder collaboration among developers, making it challenging for teams to work efficiently.
Slower development: Code smells can lead to inefficient code, slowing down development and increasing the time required to implement new features or fix issues.

Identifying and Addressing Code Smells

Identifying code smells is a skill that developers can develop over time. Some of the common methods for identifying code smells include:

Code reviews: Collaborative code reviews can help identify code smells, as multiple developers examine the code from different perspectives.
Automated code analysis tools: Tools like linters ("Lint is the computer science term for a static code analysis tool used to flag programming errors, bugs, stylistic errors and suspicious constructs."), static analyzers, and code quality metrics can identify potential code smells.
Experience and knowledge: Experienced developers tend to recognize code smells based on their familiarity with best practices and patterns.

Addressing code smells is a crucial part of the software development process and involves refactoring the code to improve its quality. Addressing code smells early helps in creating cleaner, more maintainable, and efficient code.

Common Smells

Bloaters

Bloaters are slow-growing code smells that gradually make code hard to work with, read and test. Addressing bloaters is an essential part of maintaining clean and efficient code. By recognizing these code smells and taking action to refactor your code, you can enhance the quality and maintainability of your software projects.

Example: A class that accumulates numerous unrelated methods over time

Long Parameter List

A Long Parameter List is a code smell where a method or function takes an excessive number of parameters. Long parameter lists can make the code harder to understand, maintain, and test. They often indicate that a function is trying to do too much and may need refactoring.

Example: A method that calculates an employee's salary, taxes, bonuses, deductions, and benefits all in one call, requiring ten parameters

Primitive Obsession

Primitive Obsession occurs when developers rely too heavily on primitive data types (e.g., integers, strings) to represent domain-specific concepts. Instead of creating custom classes or structures, they use basic data types for everything. This can lead to less expressive and maintainable code, as well as a higher risk of introducing bugs.

Example: Using a string to represent a customer's address, instead of creating a dedicated Address class with structured fields for street, city, and postal code, is an example of Primitive Obsession.

The important part of avoiding Primitive Obsession is encapsulating those primitives into well-defined objects that actually represent their meaning.

Benefits of Primitive Obsession Refactoring:

Primitive obsession refactoring brings domain properties and their validation logic together.
Creating classes for each behavior helps decoupling code.
Following the Single Responsibility principle (SRP).

Data Clumps

Data Clumps refer to groups of data items that frequently appear together in the code. When you see the same set of parameters or variables used in multiple places, it might be a sign of a data clump. Extracting these related data items into a common structure can improve code readability and maintainability.

Examples:

Class Level: A Customer class has separate fields for firstName, lastName, email, and phoneNumber, but these fields often appear together in other parts of the application. Grouping them into a ContactInfo class would be a better design.
Method Level: A method takes multiple parameters, such as street, city, state, and zipCode, which are always used together. Creating an Address class to encapsulate this data would eliminate the clump.
Variable Level: A function maintains separate variables for totalAmount, taxAmount, and discountAmount throughout the code. Storing them in a PriceDetails structure would improve clarity and maintainability.

Long Class

A Long Class is a class that has grown too large and contains an excessive number of methods, fields, or properties. This can make the class unwieldy, difficult to understand, and challenging to maintain. Breaking down long classes into smaller, more focused classes can help improve code organization.

A Long Class can become problematic in several ways:

Low Maintainability: Small changes in the code might affect multiple unrelated parts of the class, increasing the likelihood of introducing bugs. Developers also tend to avoid making changes to large classes for fear of breaking other functionality.
Poor Readability: A class with many methods and properties can become overwhelming, especially for new developers. The class can be difficult to navigate and understand, making it harder for teams to collaborate effectively.
Violating the Single Responsibility Principle (SRP): A long class is often a sign that it's trying to do too much. If a class has too many methods and properties, it likely has multiple reasons to change, violating this principle and making it harder to reason about.
Difficulty in Testing: Testing a large class can become cumbersome, as it may require a lot of setup to test a single piece of functionality. Since it has many responsibilities, it can lead to tightly coupled code, making it difficult to isolate parts of the class for testing.

Long Method

A Long Method code smell occurs when a function or method is overly long and contains too many lines of code. Long methods can be challenging to comprehend and debug. Refactoring long methods into smaller, more focused functions can make code more readable and maintainable.

Often, we look for the perfect solution, when a general one would often be much better.

Dispensables

Unnecessary code that should be removed from the source.

"Dispensables" are a category of code smells that refer to elements in the codebase that are redundant or no longer serve a purpose. Identifying and addressing dispensable code is crucial for maintaining a clean and efficient codebase. In this article, we'll explore some common types of dispensables:

Comments and Disabling Code

Comments and Disabling Code refer to instances where developers use excessive comments to explain code or include code that is disabled but left in the source files. The practice of commenting out code, to save it or reuse later, is bad! In most cases, it will not be reused and just take up space. Good code should not need comments to explain itself, it should just explain it by itself :) . So usually no code needs comments, if so try to write better code, better naming, better extractions, etc. Of course, XML comments for meta-data are recommended, these should follow a coherent and standardized form and wording and are not regarded as "dispensable".

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Dead Code

Dead Code is code that is no longer executed or reachable in the application. It includes unused variables, functions, or entire code blocks that serve no purpose. Dead code not only clutters the codebase but can also mislead developers and add unnecessary complexity. Cleaning up dead code is essential to keep the codebase clean and maintainable.

Duplicate Code

Duplicate Code occurs when the same or similar code blocks are present in multiple places within the codebase. This redundancy can lead to maintenance challenges, as any changes must be made in multiple locations. Identifying and eliminating duplicate code helps in reducing the risk of introducing inconsistencies and makes the code more maintainable.

Lazy Class

A Lazy Class is a class that contributes little or no value to the codebase. It may contain only a few methods, fields, or properties and doesn't serve a clear purpose. Such classes can be removed or refactored to simplify the codebase and improve its overall structure.

Speculative Generality

Speculative Generality occurs when developers include code, features, or functions that are not currently needed but are expected to be needed in the future. This can lead to over-engineering and unnecessary complexity. Removing or deferring such generality until it's actually required can simplify the codebase.

Couplers

"Couplers" are a category of code smells that relate to the interactions and dependencies between different parts of the code. These code smells often indicate tight coupling, which can lead to reduced maintainability and flexibility. In this article, we'll explore some common types of couplers:

Feature Envy

Feature Envy occurs when one class or module excessively uses the methods or properties of another class. It suggests that one class is too dependent on the internals of another, potentially leading to maintenance challenges. Reducing feature envy can help improve code modularity and encapsulation.

public class Customer {
    public string Address { get; set; }
    public string City { get; set; }
    public string Country { get; set; }
}

public class Order {
    public Customer OrderedBy { get; set; }

    // Problem: This method exhibits feature envy by accessing multiple properties of Customer directly.
    public string GetOrderAddress() {
        return OrderedBy.Address + ", " + OrderedBy.City + ", " + OrderedBy.Country;
    }
}

Better:

public class Customer {
    public string Address { get; set; }
    public string City { get; set; }
    public string Country { get; set; }

    // This method encapsulates the behavior related to the Customer's address.
    public string GetFullAddress() {
        return Address + ", " + City + ", " + Country;
    }
}

public class Order {
    public Customer OrderedBy { get; set; }

    // Now Order delegates the address formatting to Customer, resolving feature envy.
    public string GetOrderAddress() {
        return OrderedBy.GetFullAddress();
    }
}

Inappropriate Intimacy

Inappropriate Intimacy refers to excessive dependence between two classes or modules. It occurs when classes or modules become too tightly coupled, making it difficult to change one without affecting the other. Reducing inappropriate intimacy can lead to better modularity and maintainability.

Divergent Change

Divergent Change happens when a class or module requires multiple changes for different reasons. When one class or module is impacted by several changes that don't logically belong together, it can lead to confusion and difficulty in maintaining the code. By isolating the responsibilities of a class or module, divergent change can be minimized.

Shotgun Surgery

Shotgun Surgery is the opposite of divergent change. It occurs when a single change in the codebase requires updates to multiple classes or modules. This can lead to code fragmentation and introduce bugs in various places. Reducing shotgun surgery involves breaking down classes into smaller, more cohesive units.

Tight Coupling

Tight Coupling occurs when different components of the system are highly dependent on each other. In tightly coupled systems, changes to one component often require changes to others. This increases the risk of introducing bugs when making modifications and makes it harder to test individual components. By aiming for loose coupling, developers can achieve better modularity, flexibility, and easier maintenance.