Best practices are guidelines for writing good quality, maintainable, efficient, and productive code. They help developers avoid a lot of pitfalls. They can improve the development process and the quality of the software being built. In this blog, we will discuss 20 best practices of software development that every developer must follow to improve their development process and the success of their project.
Adopting a Version Control System
The Role of Version Control
A version control system (VCS) is a rite of passage in modern software. A tool such as Git helps developers track changes in their codebase, collaborate with other developers, and keep track of the history of the project. This is important when working on the evolution of a codebase, especially in a team environment, where it’s not uncommon for multiple developers to make changes to the same codebase at the same time.
One of the major advantages of version control systems is that they provide a safety net in case something goes wrong: the developer can always go back to an older version of the project. This is especially useful in situations where new features or bug fixes are to be tested but might fail or cause problems. VCS tools also make the branching and merging of the different versions of the project easy. One can branch off a portion of the codebase to work on some feature or fix some bug without interfering with the main line of development and then merge it back when the work is done.
A version control system is only as useful as its users make it. The first rule of thumb is to use a VCS for every project you work on, no matter how small. Then there’s the question of commit messages: make them consistent, descriptive, and meaningful; each message should explain the changes you’re making, which makes the history of the project much more understandable for others (but also yourself) when you finally have to wrap your mind around it.
Finally, when it comes to branching strategy, try to use something like GitFlow or a similar branching model when managing development, feature, release, and hotfix branches. This will turn your version control system into a reliable, easy-to-use, understandable, and traceable tool for storing your code, making it much easier to keep your codebase clean, understandable, and recoverable—and, ultimately, making your development cycles smoother and your codebase more robust.
Writing Clean and Readable Code
The Value of Code Clarity
This is why the holy grail of maintainable software development is clean code—code that is easy to read and understand. Writing clean code helps not only the author but also anyone else who might have to work on the project in the future. It can significantly reduce the cognitive load involved in understanding what the code does, often leading to faster debugging and fewer mistakes.
This includes adhering to naming conventions and formatting guidelines. For example, it’s helpful to choose variable and function names that are descriptive enough so that a reader can understand what the variable or function does without having to read further comments. For example, if a variable is named x, don’t name it that. Name it something more descriptive, like total amount or user age.
Having consistent indentation and spacing is also helpful because it makes it easier to see the structure of the code. It’s easier to spot a for loop if it’s indented further than the surrounding code. Linters are tools that can be used to enforce these conventions. If you have a linter set up, it will flag any problems and can even fix them automatically for you.
Another aspect of clean code is to avoid complex structures. It’s tempting to try to write clever one-liners, but usually, such solutions are less readable than straightforward ones. Try to stick to the obvious and use basic building blocks. Breaking complex logic into smaller functions or methods is another way to keep the code easy to read and, hence, easier to test and debug. The code is written once but read many times. The cost of investing in readability is repaid many times over time as maintenance and collaboration efforts are easier.
Implementing Code Reviews
The Benefits of Peer Review
Code reviews are fundamental to maintaining code quality and building a culture of collaboration within a development team. When your peers review your code, they might find bugs, identify anti-patterns, or generally improve the quality of the code before it makes it into the main branch. Code reviews are also a great way for team members to learn from each other.
One of the main advantages of code reviews is that they provide a second pair of eyes on the code, making it more likely that problems can be found that the original author might have missed, like edge cases, performance issues, security vulnerabilities, and so on. That’s why code reviews also serve as a first line of defense for applying coding standards, thus ensuring a consistent codebase that is easier to maintain over time.
For your reviews to be effective, the feedback you offer should be targeted at suggesting how to do something better. Don’t just point out what’s wrong; suggest how something could be improved. If you see four things you think could be changed, point out the two most critical issues. You might need to go into detail, but never make the review too overwhelming for the reviewer or the author.
To make sure you cover everything you should, create a checklist of what should be looked for in a review—should the code follow the coding styles, is the logic in the code correct, and are there any ways this could be optimized? Each team will develop a list of what should be checked during the review. Create a positive, supportive culture of good code review within your team, and teams will ensure that every piece of code is as good as it possibly can be.
Embracing Test-Driven Development (TDD)
The TDD Approach
Test-driven development (TDD) requires that you write tests before you write code. The advantage is that it forces you to think about what you should be writing and ask yourself the right questions upfront before you get into the weeds of implementing a solution.
The TDD process follows a cycle of writing a test for the next bit of functionality, then running that test to see it fail, writing the smallest possible amount of code to pass the test, and then refactoring the code while running the test to make sure the refactoring works. This cycle of write-test-implement-refactor keeps the code clean and stable. The main benefit of TDD is that it gives you a bed of nails that you can run anytime you make a change, so you don’t have to worry about any new code-breaking existing functionality.
The discipline of TDD is that you only work on those classes and only those methods that need writing to pass the tests you have written. You keep your tests and your code as focused and small as you can so that you can run your complete test suite quickly, get the fast, deterministic feedback you need, and easily grasp the meaning of each test.
As your test suite grows, you will find that you end up with a test suite that has high coverage of your code, and it will become easier to refactor and extend your code confidently. TDD will slow you down initially, but it pays off in spades. You will end up with less buggy code, more maintainable code, and a high-coverage test suite.
Prioritizing Automated Testing
Ensuring Code Reliability
Automated testing is critical to maintaining a clean codebase, as it ensures that changes don’t creep into regressions or bugs. Automating tests allows developers to quickly and consistently verify that a given piece of code behaves as expected. Since test runs can be sped up by an order of magnitude over manual testing, automated tests can also be run much more frequently, providing instant feedback about the effects of changes and allowing teams to catch issues during the early stages of development.
Another best practice is to develop full test cases so that testing encompasses as many different scenarios as possible, especially edge cases and potential failure points. For example, you can create unit tests (to test individual components), integration tests (to test how parts of a system connect), and end-to-end tests (to simulate how a system will handle what a user can do). Testing frameworks such as JUnit (for Java), PyTest (for Python), or Jest (for JavaScript) can also make test creation and execution easier.
Integrating these tests into the Continuous Integration/Continuous Deployment (CI/CD) pipeline provides even more benefits. Every time an engineer commits code or opens a pull request, they can automatically rerun the tests against their changes to make sure that the test suite still passes. The results can be displayed as part of the CI/CD pipeline, helping engineers gain confidence that their work is more likely to pass all tests when merged into the main branch. CI/CD makes it safer to refactor code and fix bugs by reducing the risk of accidentally breaking existing functionality.
Utilizing Continuous Integration/Continuous Deployment (CI/CD)
Streamlining the Development Process
Continuous integration (CI) and continuous deployment (CD) are two very helpful automation techniques that are part of the DevOps approach. CI automates the build and test processes so that any changes to code are automatically built and tested systematically as soon as they are committed to the repository. A well-defined and automated test suite is used to test the correctness of the changes and to ensure that any new changes integrate correctly with the existing functionality of the system.
CD extends CI by automating the deployment of the changes to production, for example, by setting up automatic and seamless deployment and test stages in the production environment after each commit. This allows changes to be deployed more frequently and with greater reliability.
The key advantage of CI/CD is that consolidating the workflow shortens the time between the code being written and shipped into the hands of users. CI/CD can reduce manual errors, improve code quality, and accelerate the delivery of code to production thanks to the automation of testing and deployment. Furthermore, CI/CD pipelines allow teams to identify and remediate issues earlier in the development cycle, which in turn reduces the cost and complexity of fixing bugs.
Setting up your CI/CD pipeline involves planning and configuration. First, configure your CI pipeline so that it runs automated tests on every change before merging into the main branch of the codebase. Configure your CD pipeline so that changes are deployed to a staging environment for further validation before being pushed into production. Automate all processes using tools such as Jenkins, Travis CI, or GitHub Actions to ensure reliability and efficiency. CI/CD practices enable teams to have faster, more reliable deployments with high code quality throughout the lifecycle of development.
Documenting Code and Processes
The Importance of Documentation
Documentation is a core principle of good code that facilitates following and understanding a project, often reducing the need to actually go to the source code for answers. This makes it possible for developers to be up and running in a fast and effective way. It will also help future developers who pick up the code after the original developers have moved on.
So, first, write inline comments that explain the why and how of the most complex or non-obvious sections of code. (But don’t comment all over the place—your code should be so obvious that you don’t have to explain it all the time.) Write API documentation that lists all the functions, classes, and modules in your project, along with their parameters, possible return values, and usage examples.
Besides code comments, I also write documentation at higher levels, such as architectural overviews, design patterns, and user guides. Such documentation provides the background of how the system comes together as a whole and how to extend or modify the system in the future. For example, there are tools—such as JSDoc for JavaScript, Sphinx for Python, or Doxygen for C++—that can automatically extract documentation from comments in the code. Documentation makes the project more sustainable over the long term.
Applying the DRY Principle (Don’t Repeat Yourself)
Reducing Redundancy
The DRY principle (‘Don’t Repeat Yourself’) is a software engineering mantra to reduce redundancy and maintainability problems in code. To paraphrase programming folklore, every statement must have a single, unambiguous interpretation within a computer program. There should be only one copy of any particular piece of knowledge or logic. All too often, code is copied and pasted across a codebase at great cost. This is highly problematic since repeating code in several locations introduces errors, makes the codebase harder to maintain, and extends the maintenance burden for changes across multiple places.
The DRY principle aims to eliminate duplicate code as much as possible. For example, if you find that you’re using the same block of code in several different places, try to extract that block into a new function, class, or module that can then be invoked wherever it’s needed. Not only does this reduce the overall amount of code, but it also makes it easier to update or debug. If you need to change something, you only have to do it in one place rather than in each block of repeated code.
Of course, functions and classes aren’t the only abstractions you can use to reduce repetition—modules, for example, can help you group together related functionality. If your app has a collection of utility functions that are used in several places, put them in a ‘utility’ module or library. Not only does this help you adhere to the DRY principle, but it also improves the organization and readability of your codebase. By consistently applying the DRY principle, you end up with a more maintainable, scalable, and robust codebase that is easier to work with and modify.
Practicing YAGNI (You Aren’t Gonna Need It)
Avoiding Overengineering
The principle is an acronym for ‘You Aren’t Gonna Need It.’ It’s a sensible guideline for developers to stick to the bare minimum of functionality in a codebase—i.e., ‘just enough’—and resist the temptation to code for potential future functionality that might never end up being needed. Overengineering can add unnecessary complexity, just-in-case functionality, prolonged development time, and hard-to-maintain code.
To practice YAGNI is to be ruthless and stay focused on the task at hand. If you’re building a feature that only needs a partial-blown, heavily configurable system, don’t build one. That’s over-engineering. Implement the simplest thing that could work. Later, the feature will need more sophistication, refactoring, and expansion of the code.
The most critical benefit of YAGNI is its potential to keep development lean and mean. If you are writing only what you need, you are less likely to write code that is either unwieldy or convoluted. Consequently, you’re less likely to introduce bugs, and you’ll be faster in delivering value to your customers—you aren’t working on something that no one needs. If you practice YAGNI, you can have a clean and focused codebase that will grow naturally rather than hypothetically to respond to real needs, not imagined ones.
Ensuring Code Modularity
Building Modular Software
Modularity is one of the principles of software engineering billing, in which a system is decomposed into smaller, self-contained parts—modules. Each module has its own part of functionality (e.g., module for user authentication) and can be developed, tested, and maintained separately. Modularity not only makes the code easy to understand but also provides improvements for maintainability, scalability, and flexibility.
When designing modular software, you should use separation of concerns. Each module should perform a single aspect of the system’s functionality without overlapping responsibilities. A web application might have a module for user authentication, a module for data access, and a module for user-interface rendering.
Equally important is the single responsibility principle, which states a class or module should have a single reason to change. This reduces the likelihood that a change will introduce a bug and makes the code more deterministic and testable. A modular system is also much easier to scale because individual modules can be refactored, replaced, or extended, and the rest of the system is not affected. By focusing on modularity, you develop software that is more robust, agile, and maintainable, which leads to easier updates and faster development cycles.
Refactoring Regularly
Improving Code Quality Over Time
Refactoring is the process of changing a system’s internal structure while leaving its external behavior unchanged. It is a key part of software design and must be done continuously. The aim is to improve the design of existing code: remove duplication, enhance modularity, simplify structure, avoid tangles and long methods, and so on. These improvements make the code easier to understand and maintain in the long run, so refactoring is an important part of keeping a codebase healthy. It gets rid of technical debt, reduces complexity, and resolves any code smells.
Look for code that is hard to understand, duplicates logic, or is prone to bugs. These are all likely symptoms of something deeper, and they’re all ripe for refactoring. Refactoring might be as simple as renaming a variable or function to make its purpose more visible. It might involve restructuring a class or module into more logical blocks. It could be part of a broader effort to simplify complex logic. The important thing is that it’s done in small, incremental steps that keep the codebase consistently improving.
There is a certain discipline that comes with introducing refactoring into the normal development workflow. This is why it’s useful to set up dedicated refactoring sessions, for example, at the start of the day, or to organize refactoring tasks as part of the normal workflow. The process of refactoring serves to keep the codebase of a project clean as the project progresses through its feature life cycle. This may seem like ‘waste’ in the short term. Still, the long-term benefits of reducing technical debt, thereby making application code more maintainable and ultimately increasing development speed, are the real gains.
Keeping Dependencies Updated
Managing Software Dependencies
In the context of modern software development, much of a larger project’s functionality can be brought in from the outside in the form of libraries and frameworks. These can be used to speed up development, leverage others’ work, and ensure developers are using best practices. However, every one of these dependencies has to be maintained in order to keep the software itself secure, stable, and performant. If dependencies are not updated regularly, they are very likely to introduce security vulnerabilities, compatibility issues, and bugs that could be avoided by keeping them up to date.
For example, when it comes to dependencies, start by making sure you’re taking full advantage of package managers to download and update your libraries (e.g., npm for JavaScript, pip for Python, Maven for Java, etc.). Many package managers even provide commands to display a list of outdated packages and, in many cases, can even automate the update process. When you do find that a dependency has been updated, read the release notes for the new version to see what’s changed, and test your app thoroughly after updating to make sure things still work as expected.
Besides regular updates, use tools that track your dependencies for known vulnerabilities, such as Dependabot or Snyk. Such a tool can inform you if a dependency has a security issue and either recommend or even automate the upgrade. By keeping dependencies up to date, not only will your software be safer, but it will also benefit from new features, optimizations, and bug fixes of the newer versions.
Prioritizing Security in Development
Building Secure Software
Security should be an integral part of every aspect of the software development lifecycle, from the very first line of code through to the final release. In the face of escalating cyber threats, securing software from the outset is better than trying to bolt it on at the end. Creating secure software means taking steps to prevent vulnerabilities, protecting access to data, and ensuring the privacy and integrity of data.
One of the core coding best practices for security is input validation. Input validation means that all input must be validated prior to processing, and this can help avoid a lot of common security vulnerabilities such as SQL injection or cross-site scripting (XSS), which are ways to inject dangerous data into a website’s database or code and then use that data to gain access to sensitive information or perform unauthorized actions. Use parameterized queries, sanitize user input, and never trust an external source of data unless you verify it. Also, always adhere to the principle of least privilege. This means that you give the minimum amount of access to a user or system necessary to perform its job functions.
An important part of this is encryption: all sensitive data, both at rest and in transit, should be encrypted using strong algorithms, such as passwords, personal data, and communication between client and server. Another aspect is running regular security audits and code reviews that look for vulnerabilities. The goal here is to catch vulnerabilities before they are found and exploited and to ensure that your software remains secure from development through deployment.
Using Code Metrics and Analysis Tools
Measuring Code Quality
Through code metrics and other analysis tools, you gain insight into the quality, maintainability, and complexity of your codebase. Examples of metrics include coupling and cohesion, which indicate how tightly code is tied and how well it performs its intended purpose, respectively. Using this type of metric, you can determine how well your system is structured and whether it is suffering from code smells, technical debt, or performance bottlenecks.
There are a number of different types of code metrics that could be used. For example, cyclomatic complexity measures the number of completely independent paths through a function or method. It is correlated with how difficult it is to understand and test. High complexity may be an indicator that a function needs to be refactored into smaller, more manageable pieces. Others, such as code coverage metrics (the percentage of your code that’s covered by automated tests), can be helpful. In general, the higher the coverage, the more reliable the code is. However, you should pay attention to meaningful coverage, not just ‘coverage’ as a raw number.
Code-quality tools like SonarQube, CodeClimate, or ESLint can calculate metrics for you and generate feedback explaining how you can improve your codebase. You can integrate these tools into your CI/CD pipeline to track how your codebase’s quality changes over time or even enforce coding standards automatically. Especially when you measure your code quality regularly, you can identify bugs and hotspots early, solve them before they pile up, and keep your codebase healthy and maintainable.
Writing and Maintaining Unit Tests
The Role of Unit Testing
Unit tests are crucial for checking whether each component of your software is working correctly and whether it remains so as your codebase evolves. Unit tests focus on individual functions, methods, or classes so that you can isolate and test each one in turn. It would be best if you wrote them before you built the code you’re testing and then ran them soon after. Unit tests are the best way to catch bugs when they’re still tiny.
Unit tests need to cover as much ground as possible, particularly edge cases. Each test should be isolated (that is, it shouldn’t rely on external systems or states) so that it can be run independently, repeatedly, and consistently. Tests can be mocked and stubbed so they aren’t dependent on external interactions. Mocking allows you to test your unit in isolation by replacing real external dependencies with fake implementations. Stubbing, on the other hand, involves replacing real dependencies with canned responses. It would help if you also kept tests up to date as your code evolves.
When you refactor, add new features, or make changes, you might break existing tests that cover those areas. As a rule of thumb, if you make a change in the code, you should update or write unit tests for that section of the app. Embedding unit tests into the development process will build a safety net, which will help you maintain high-quality code while ensuring continuous development.
Implementing Error Handling and Logging
Managing Errors Gracefully
Good error handling and logging are two of the most important aspects of reliable software development. Proper error handling addresses the ‘what happens if something goes wrong’ situation, and good logging allows developers to keep track of what went wrong and why.
To build robust error handling, first define a consistent approach to dealing with different types of errors, including input validation errors, network failures, exceptions, etc. Catch errors at appropriate levels of the application using try-catch blocks or similar mechanisms. User-facing messages should be clear and actionable without exposing too much information.
Set up logging to capture errors, warnings, and other significant information with as much context as possible to aid diagnosis and recovery. Consider using structured logging formats and centralized logging systems to aggregate logs across different parts of the application and facilitate monitoring and analysis of system behavior. Making error handling and logging a priority leads to more resilient software that can detect, diagnose, and recover from problems quickly.
Ensuring Cross-Browser and Cross-Platform Compatibility
Reaching a Wider Audience
In the current landscape of a multitude of different browsers, devices, and platforms, your software must be usable on all these platforms, irrespective of the version or user environment.
Compatibility requires testing across multiple browsers (Chrome, Firefox, Safari, Edge) and devices (desktop, tablet, smartphone). Tools such as BrowserStack or CrossBrowserTesting can replicate these environments to verify that you can catch the bugs that come from differences in rendering engines or device capabilities. Less reliant on the user’s choice, you can also follow web standards and use responsive design techniques that help the software adapt to screen size and input devices. Fixing compatibility problems early can save time and avoid alienating users who aren’t willing to install new software and start from scratch on their preferred platforms.
Managing Technical Debt
Balancing Speed and Quality
Technical debt is a term originally coined by Ward Cunningham to describe the compromises made during the development process that trade-off short-term code quality for quick fixes or shortcuts. While some technical debt is expected in the development of any software system, it must be carefully managed and paid down over time to maintain the project’s health and avoid adding a great deal of debt that will hamper the system later on.
Balancing speed and quality requires deliberate decisions about when to incur technical debt and when to pay it back. Perhaps you had to ship a feature quickly, but when you get breathing room, you make sure to go back and clean up the code or correct the shortcuts you made. Writing code reviews and refactoring sessions into your schedule can help uncover areas of technical debt and identify which to prioritize. Keeping a clear understanding of the trade-offs involved in each decision can also help prevent technical debt from growing out of control. By maintaining a healthy codebase that can scale and be maintained long-term, you’ll know that you’ve effectively managed technical debt.
Encouraging Collaboration and Communication
Fostering a Collaborative Environment
Suppose you want to succeed at any software development project. In that case, all your team members should have the ability to work together and communicate freely with one another. They can share their knowledge, work out their differences faster, and always keep the same direction.
Collaboration is encouraged by using tools that facilitate communication, such as Slack for real-time message communication, Jira for task management, and GitHub for code reviews and version control. Additionally, regular meetings such as daily stand-ups, sprint planning, and retrospectives provide a space to stay up-to-date and talk about problems or blockers. An open culture where team members feel safe speaking up with suggestions, questions, and feedback is also vital for collaboration. In short, by placing more emphasis on communication and collaboration, the team stays in sync. It works better together, enabling them to create better software.
Continuously Learning and Improving
Staying Current with Industry Trends
Software development is a rapidly changing field. New tools, languages, frameworks, and best practices are released constantly. In order to be competitive, deliver high-quality software, and stay on top of the wave, developers must constantly learn and improve themselves.
There are many ways to keep abreast of new technologies and keep learning, such as attending conferences, participating in workshops, following blogs or online communities (for example, in software engineering, Stack Overflow, or GitHub), practicing new tools and technologies in side projects or hackathons, or anything else that might keep you up to date.
Secondly, continuous learning also helps with keeping you flexible. It is nice to know that you can always pick up new things or familiarize yourself with new languages or paradigms, thus opening new doors for you. Last but not least, keeping up with new technologies and having a continuous learning mindset also guarantees that your practices of development remain cutting-edge so that you can fully contribute to your team’s or your projects’ development efforts.
Conclusion
As a result, applying best practices in software development—such as designing additional layers for managing complexity, using software patterns and convention over configuration, as well as thinking about the project as a whole—can greatly help all participants create higher-quality, more maintainable, and more efficient software. This will not only help performance in the short term but also make maintenance easier and enhance collaboration over the entire lifecycle, ultimately increasing the likelihood of the project’s success and sustainability.
