Writing code that’s easy to read and understand is essential to ensuring clean code. This enables others to comprehend its purpose at a glance. Writing clean code makes it simpler to follow the logic, aiding other developers in understanding it. The clarity of the code enhances its maintainability, as programmers can confidently make changes, knowing precisely what the code does. A codebase that follows clean practices is well-named, well-structured, well-formatted, refactored, and well-tested.
Developers play a crucial role in the ‘clean code’ movement. They are encouraged to use meaningful names, proper indentation, and avoid duplication. It’s common for developers to rename a variable without much thought once they understand it, but this can make the code less meaningful in the future. Additionally, if another developer takes over the code, the code must be easily understandable. Writing code that others can easily comprehend is a significant responsibility for developers. By doing so, they can understand the code simply by reading it without deciphering it. Clear, readable, and easy-to-modify code is the hallmark of clean code. Teams can collaborate more efficiently by avoiding unnecessary complexity and repetition and adhering to best practices. This code is a pleasure to read, understand, and update. Clean code is also less prone to errors and bugs, as the ‘cleaning’ process minimizes potential problem areas. While clean code does not guarantee error-free, performant, or scalable code, it is a crucial step in that direction. Writing clean code is essential for smooth development and to prevent common errors.
Software maintenance involves fixing undiscovered errors from earlier development phases, upgrading features, and ensuring operational safety. It can take up to 65% to 75% of the software’s lifecycle effort. Writing clean code makes it easier and faster for future maintainers to modify the software, thus enhancing productivity at later project stages. Many people contribute to projects, resulting in different coding styles that can be difficult to understand. When writing clean code, the author considers others’ ease of understanding and accessibility as well as his or her experience.
Coding is one way a programmer’s expertise manifests itself. When reviewing code written by another programmer, an individual can determine another programmer’s level of professionalism through details such as how comments are written, the naming conventions, and the structure of their project. The software development process must be reflected in the source code, representing the team’s effort and professionalism. The source code showcases team quality, operational procedures, and management skills. A clean code writer needs the right attitude, knowledge, and practical experience to write good code.
There are several ways to ensure our code is “clean,” but most developers can agree on a few fundamental guidelines. It is essential to remember that these are guidelines rather than rules. Coding has no strict rules. It compiles. It runs. These guidelines are intended to assist developers in writing, understanding, troubleshooting, extending, and enhancing their code. Coding standards facilitate team collaboration. When a convention seems unreasonable, consider discussing it with your team rather than breaking it alone. In programming, KISS stands for “Keep It Simple, Stupid! “People resort to complex design patterns and algorithms without considering more straightforward options.
The Boy Scout rule is generally important regarding clean code. It says, “Leave the code cleaner than you found it.” Whenever you encounter a Code Smell, replace the code with clean code to prevent similar problems from occurring in the future. Although this may require additional effort, it will reduce long-term maintenance costs. As a result of time constraints, programmers tend to fix symptoms rather than fix the underlying cause of errors, which can cause out-of-place code that interrupts the logic of functions, classes, or even entire packages. This principle refers to not duplicating knowledge or business logic within a program. In most cases, code duplication is acceptable as long as the underlying knowledge or logic is not duplicated. Modifications should be done in one place. A zealous D.R.Y approach can, however, undermine the KISS principle.
Ensure the coding style and indentation are consistent. Adhering to community-accepted coding standards can make your code more visually apparent. Code sniffing tools, IDE tools that understand code formatting rules, and AI tools are all options for accomplishing this. Your codebase should be consistent, regardless of the coding style. The acronym DRY stands for “Don’t Repeat Yourself”. This principle encourages you to create functions that can be used for many tasks, simplifying your code and reducing redundancy. The benefits of this approach are manifold. Firstly, it can significantly reduce the size of your code, leading to a more compact and faster program. Secondly, it allows you to make changes in one place, providing a centralized approach to your work. Lastly, it enhances the readability and understanding of your code.
Minimalists strive to write code with as few lines and characters as possible. Perhaps it has something to do with coding games. The code you write is ultimately for humans, not computers. It would be just as simple to write in assembly or low-level language if we were writing for computers. Today’s most popular coding languages are at a higher level, meaning they are designed for human consumption and will be compiled into machine code later. Do not forget to optimize your code for you and your team. You do not have to worry about the computer. Handling errors elegantly using try-catch blocks or similar mechanisms is crucial. This approach provides constructive debug information without compromising the stability of your system. It also lets you identify potential edge cases where things might not work as expected. Equally important is creating descriptive and helpful error messages, which can be invaluable when troubleshooting problems.
Continually refining your code is a crucial practice. As understanding the project deepens, you should modify the code to enhance clarity and efficiency. However, avoiding falling into the ‘perfection’ trap with refactoring or creating code is essential. Instead, focus on creating quality code, following best practices, and solving the problem. Remember, trying to make your code ‘perfect’ can waste time. Monitoring changes in code with systems like Git makes it easier to collaborate, track history, and revert changes if needed. This is especially useful for collaborating across different workstreams in a team setting. Version control is also excellent for reducing stress and protecting yourself in case of errors or deletions. You can always go back in time to review or recover old code. To keep your code clean, keep workstreams on separate branches. If you have multiple developers working on the same project over time, you can also use Git blame it to determine who exactly wrote or changed what. In cases where you need to find someone who knows the code or offers constructive feedback to another developer, that is helpful.
While clean and high-quality code are related, they are not the same. Software quality evaluations generally involve software metrics. Code quality cannot be defined universally since it depends on context and team dynamics. The concept of code quality refers to code that meets a high standard. Individuals’ definitions of high-quality code differ, so reaching a consensus is crucial. Unless there is agreement among team members, members may interpret good code as they see fit. Several studies have concluded that code quality’s three most significant components are readability, structure, and comprehensibility. To maintain high-quality code, code smells must be minimized or eliminated.
The following characteristics indicate a code smell: rigidity, fragility, immobility, overcomplication, unnecessary repetition, obscurity, ignorance of code smell indicators, prioritising deadlines over quality, copying and pasting, and not knowing clean coding principles. Unlike clean code, Code Smell can increase maintenance costs and risks for future software expansions and maintenance. These are signs in a program’s code indicating deeper, more complex issues. In the late 1990s, Kent Beck introduced the term ‘Code Smell’ on WardsWiki, and it gained wide use after Martin Fowler wrote the book Refactoring: Improving the Design of Existing Code. Clean code principles are based on understanding and eliminating Code Smell, empowering developers to take control of their code quality. Understanding and eliminating Code Smell is the opposite of clean code.
It is important to note that code smells indicate poor design and implementation choices that hinder code understanding, modification, and maintenance. If code smells are introduced accidentally, they can create faults that make future maintenance more difficult. Duplicate code, long methods, and large classes are common examples. According to Yamashita and Moonen, around 32% of developers were unaware of code smells. Raising awareness of code smells will help developers produce cleaner code. Code smells cannot be evaluated and eliminated if programmers do not understand them. Code smells were recognised as early as the mid-1990s, and tools were developed to detect them. Although refactoring tools can provide significant benefits, many development teams must be informed about them.
Experienced programmers often encounter Code Smell, whether they create it themselves or clean it up after others. Dealing with messy code raises constant questions about its origin, significantly reducing productivity and making even more problematic code, perpetuating an inefficient cycle. Urgent attention is needed to address Code Smell in software development due to the frustration and inefficiency it causes, highlighting the need for immediate action.
Rigidity refers to the difficulty of changing any part of the software. Changing even a tiny aspect of the program might require numerous modifications elsewhere. Software is fragile because many components can break even if a small change is made to them. When one element in a program is immobile, it can cause uncontrollable errors or require too much effort to reuse. A complex algorithm, data structure, or solution can make it difficult for others to comprehend. Simply put, it is like trying to crack a nut with a sledgehammer. If not uniformly modified during maintenance or further development, unnecessarily repetitive code fragments may lead to future issues. “obscurity” describes when the reader struggles to understand the author’s intent because of confusing variable names or inconsistent steps in a function’s execution.
Several specific characteristics of the code also exist, including unnecessary length, large classes, too many parameterised functions, comments that do not help understand the code, and redundant segments that do not need to be removed. A lack of understanding or ignorance of clean code principles may mean that programmers do not know or understand how to write clean code. A lack of awareness of code smell indicators may prevent programmers from recognising the warning signs of code smell. When programmers copy and paste code into their projects, they only need to examine it thoroughly after some time. When deadlines are prioritised over code quality, programmers may feel that spending time writing clean code is unnecessary. They intend to refactor the code later, but often, “later” means “never.” Code smells are not errors or problems that prevent programs from running; instead, they indicate design limitations that can delay future development or lead to software errors.
We can apply clean code principles and practices to prevent these code smells, making writing high-quality code easier and reducing technical debt. Technical debt refers to (and often quantifies) the long-term effects of suboptimal decisions to accelerate development. It is primarily concerned with software development’s hidden aspects and challenges. Code that introduces technical debt, intentionally or unintentionally, can be more challenging to maintain and improve, resulting in increased development costs and delays. Projects that continue to accumulate technical debt become more complicated to eliminate. T.D.I (Technical Debt Issues) describes measurable cases of technical debt, of which code smells are one type.
Refactoring is proper in cases where T.D.I have already been introduced. During refactoring, the code is modified without altering the system’s external behaviour. In this case, the system’s functionality remains unchanged and works according to its design. A developer should ensure that the outcomes produced by their code or system stay the same after refactoring. Even though refactoring is often defined differently in practice, this standard definition generally applies. In practice, developers focus more on refactoring to improve code readability, maintainability, and performance than strictly maintaining external behaviour. Even though refactoring maintains existing behaviour, it can also accommodate new features or changes to architecture and design. There may be instances where the refactoring process does not preserve the original behaviour.
Principles of function writing. Always keep in mind that functions should be brief and should only perform one function. There should be no more than 20 lines in functions. It is recommended that each function line is no longer than 150 characters if this is impossible. It is easier for others to comprehend the function if you describe how it is done. In addition to predicting the steps a function will take from its signature, it is even better to know the steps it will take from its signature. Break large tasks into smaller ones when possible to keep their contents concise. In this way, users prevent unintentional side effects throughout the program. Whenever you retrieve data, you should not reset a variable’s value.
Adheres to the Single Level Abstraction principle (S.L.A) when splitting functions. There must be an equivalent level of abstraction between an abstract statement and a statement within a function. When splitting functions, the primary function should only call these smaller functions after splitting to avoid complex logic. In the beginning, functions often have few parameters. However, new parameters may be added over time, increasing the number of parameters to avoid altering the existing logic. Rather than passing individual parameters into a function, group them into a class and pass an object from that class. You should avoid controlling a function’s logic with parameters. You should instead divide the function into multiple functions, each performing a specific task.
Authors can use comments to inform readers about tasks they have completed or plan to complete. Furthermore, it may contain future tasks to be handled by a function or class, warnings about functions that might result in undesirable side effects, explanations of why a particular method is preferred when there are many options, and clarifications of why specific values are chosen for constants and variables rather than others. Certain types of redundant comments in our programs must be removed. These include code comments you no longer use or intend to reuse, functions with clear names and data types, primarily when the comments do not provide additional information, and comments on changes made during each file edit. Commenting on code is unnecessary since version control systems like Git track changes effectively.
The error codes you return can handle errors if your language does not support exceptions. Consider, however, the scenario in which programmers still use this approach, even if their programming languages support exceptions. In such cases, readers may have trouble distinguishing between an error and an actual value. In such situations, exceptions are preferred instead of specific error codes. By placing try-catch-finally at the beginning of a function, you make it clear what your intention is, where the main actions occur in the try block, while the catch block maintains consistency even when errors occur, therefore, a transaction that involves try-catch-finally is intended.
It is essential to contextualize errors by explaining where and why they occurred. Thus, programmers can trace back error information quickly to determine the cause of an error. Errors can also be further explained by defining specific error classes based on their names or properties, allowing readers to understand the context of the error. Whenever a function returns a null result, the caller must check the result before proceeding. Due to this requirement, multiple checks are performed in code, which can obscure the intent and content of a code segment. Make sure you create your wrapper functions whenever library functions return null. Wrappers can throw exceptions if they throw exceptions or return null as an alternative.
The cause of errors is often difficult to trace because programmers leave them unhandled intentionally or unintentionally. Errors should only be ignored if they do not affect the program’s operation or pose a risk to users. When errors occur, they should be handled appropriately. Keep the logic simple. Unit tests ensure the main program’s code functions correctly in software development. Nevertheless, how can we be sure that unit tests are accurate?
Is it worthwhile to write tests for unit tests? If you persist in questioning this, you may end up in an endless testing cycle. Therefore, unit tests should be written with simple logic to minimize error risk. Unit tests should follow the A.A.A pattern (Arrange, Act, Assert), contain only one assert statement in each test, and verify only one specific case per test. Unit tests ensure the main program’s code works correctly and serve as documentation. Hence, use business terms instead of programming jargon (such as data types, design patterns, etc.).
Unit tests must be fast so developers can test multiple units quickly. Reluctance to wait might lead to unit tests being run less frequently due to slow performance, compromising the program’s reliability. There should be no dependencies between tests; their success or failure should not affect each other. This independence allows tests to be run in any order and parallel.
Tests should be independent of external environments and repeatable in any environment. Put another way, do not assume the system has initial data before performing tests. Once they have been run, tests should not leave any data behind or impact other systems, and they should not rely on databases, files, or network services that may be unavailable.
Self-Validating: A test should result in a binary result, either passing or failing. Rather than requiring a manual comparison of test results, results should be immediately visible after running them. Timely: You should always test before you write production code. It is often not easy to write unit tests for existing code after it has been implemented in production. This is typically achieved through Test-Driven Development (T. D.D).
The importance of clean code principles in software development projects cannot be overstated. Organizations and teams that write clean code benefit individual programmers and the entire development team, fostering a sense of unity and shared purpose. Adhering to clean code principles allows programmers to understand better, modify, and debug their programs. This improves team collaboration by reducing technical debt, minimizing errors, and ensuring long-term stability.
To implement clean code, you must think beyond the rules and apply several practices to achieve that mindset. The goal is to create understandable, maintainable, and extensible software. Studying diverse coding practices may assist one in improving coding practices, especially those related to open-source projects. By consistently coding cleanly, software development becomes intuitive and efficient. Using these principles will allow developers to avoid the pitfalls of unmaintained, complex code, making their work more straightforward for themselves and others who might work on it.
By promoting continuous improvement and efficiency, clean code seeks to increase software quality, reduce technical debt, and inspire a culture of learning and growth. In essence, clean code promotes using code as an art form rather than a tool for completing tasks. Ultimately, clean code is an essential aspect of software development that significantly impacts efficiency, maintainability, and success.
Writing clear, understandable, and sustainable code is not enough. In addition to naming conventions, concise functions, error handling, and thoughtful comments, the clean code principles are more than guidelines. They are a path to achieving a sense of accomplishment and building robust, scalable, and collaborative systems.
