Code Quality: Definition & How to Improve Code Quality

Achieving high-quality code is essential, and it’s something every developer should strive for throughout their career. However, the concept of quality in code is highly subjective – after all, what exactly constitutes ‘good’ code, and when can one say their lines of code have been written well? More critically, how do you determine whether your code is good or bad?

In this article, we will clarify this and offer guidance, deep insights, practical examples of what good code is and methods to measure code quality. We will focus on the underlying software development practices and principles of code quality and how to maintain it for the good of the entire codebase and software project.

Code quality is the assessment of how well a piece of code achieves its purpose over time and how easy it is to maintain. In basic terms, it’s about writing code that is concise, understandable and extendable. Even more than that, its definition involves various aspects of code such as structure, performance and security.

Many developers have a common problem: they do not know how to determine the quality of their code. However, there is a set of rules known as best practices in the industry that assist in this. Code that adheres to these standards is considered quality code, while code that deviates from them might lead to issues (and even legal liabilities) later on.

Here are the key characteristics of high-quality code:

• Code readability: Other developers or a development team should be able to understand your code easily.
• Maintainability: The code should be easy to modify and extend.
• Performance: Code should execute tasks efficiently.
• Security: Make sure the code’s quality and security are maintained at a high level to avoid vulnerability.
• Testability: The code should be organized in a way that makes it easier to do tests on it.

By focusing on these attributes, developers can ensure they are writing high-quality code that serves its purpose effectively and stands the test of time.

So, why code quality is important? Low-quality code can cause a range of issues, from difficult-to-fix bugs to security vulnerabilities. It does not only constrain your pace of development — it also increases future costs. Poor quality code not only causes immediate issues, it also leads to significant costs over time and requires extensive resources to address these recurring problems and implement fixes. Even a minor issue can snowball, which may result in system inefficiencies and costly errors.

Consider a scenario in which there is a small mistake in an unrefined code that results in a total crash of a system. Would it not have been better to avoid the scenario by using proper coding practices?

High-quality, maintainable code helps ensure the following:

• Fewer bugs. Well-written code is easier to debug with fewer issues.
• Faster development. Pieces of software code that follow code quality standards are simpler to understand, which reduces time spent by developers on fixes of potential issues.
• Better collaboration. High-quality code makes it easier for teams to work together on the same codebase.
• Long-term sustainability. Software built with clean code is easier to maintain and scale as requirements evolve.

Ultimately, improving this parameter should be a top priority for any software development project because it directly impacts the efficiency and scalability of the system.

How do you measure code quality? When performing an analysis on the quality of the code, there are clear indicators of what constitutes good or bad code. Good code is simple, efficient and easy to read. Bad code is cluttered, overly complex and difficult to maintain.

• Traits of good code

  • Follows consistent coding quality practices such as appropriate variable naming and simple logic.
  • Is thoroughly documented. ​​Good code includes proper comments and documentation that explain the purpose and functionality of each part. This makes it easier for other developers (or even your future self) to understand and work with the legacy code.
  • Adheres to the DRY principle. The “Don’t Repeat Yourself” (DRY) principle is a hallmark of good code. By reducing redundancy and code complexity while also writing reusable functions, good code minimizes the potential for bugs and makes future updates easier. With concise code, changes only need to be made in one place instead of multiple spots in the codebase.

• Traits of bad code

  • Contains unnecessary complexity, making it hard to debug.
  • Lacks comments, which leaves other developers guessing the purpose of specific blocks.

  Performing regular code quality checks and using code quality testing tools can help detect bad code early in the process, preventing long-term technical debt.

It is essential to know how to evaluate the quality of code because code quality management and improvement follow its evaluation. There are areas that the developers need to focus on in order to write more maintainable and secure code and ensure code hygiene. 

There exist a number of relevant metrics that are useful in assessing software code quality. These software code quality metrics address parameters of the code such as structure, readability and performance. When these metrics are tracked, teams maintain order and control over the quality of code throughout the development process.

Cyclomatic complexity

This metric determines the complexity of code and measures the number of possible paths that can be taken through a certain piece of code. Testing and maintenance of code are complicated with increased complexity. Lower cyclomatic complexity means that quality code is easier to comprehend.

Code coverage

This metric assesses how much of the code is covered by automated tests. If a high percentage of code coverage is achieved, then most of the source code has been tested, reducing the likelihood of undiscovered bugs. While 100% coverage is not always necessary, aim for a fair proportion of coverage because that means that your tests will be able to identify the bulk number of issues. Without adequate test coverage, even small changes can introduce unintended consequences, which can lead to poor code quality.

Code duplication

Duplicate code is a major red flag for quality. When sections of code are copied and pasted multiple times throughout a project, it becomes difficult to maintain, and you get bad-quality code. If a bug or necessary update is discovered in one instance, developers must track down and fix every occurrence. This bloats the codebase and code style and makes long-term maintenance more challenging. The code review process to identify and eliminate duplication is a key step in achieving better maintainability and source code quality.

Maintainability index

This metric evaluates how easy it is to maintain the code. Factors like complexity, length of code and the presence of comments and documentation all contribute to this index. A higher maintainability index means the code is simpler to modify and adapt, which is essential for long-term sustainability.

Halstead metrics

These metrics are based on the number of operators and operands in the code, offering insights into the difficulty, volume and effort required to understand or modify the code. While this might sound technical, in simpler terms, Halstead metrics shows how much cognitive effort the code requires on a developer when working with it. If the metrics indicate that the code is too complex, it suggests the need for refactoring.

Defect density

This metric assesses the number of code defects or bugs in relation to the size of the codebase or source code. The lower the figure of the defect density, the better the quality of the checked code because it possesses fewer bugs and is considered more stable and trustworthy. In addition, monitoring defect density through the years can be a good tool for teams to assess whether all efforts to enhance code quality were fruitful.

Improving code quality is not a one-time task, but rather a practice that incorporates different strategies and several best practices. The following are some of the most efficient techniques we at DevCom have found to encourage improvement over time.

1. Establish and follow code standards

One of the simplest methods to ensure developers do not lower their standards is to establish clear standards for code development. This makes sure everyone adheres to the same rules when writing clean code, which drastically simplifies the work process. These standards must cover everything from variable naming conventions to how functions are structured. For example, adopting conventions such as CamelCase for variable and method names or a defined system for constructing code should ensure orderly processes. Consistent style and bug-free code is much easier to maintain, debug and enhance over time.

2. Use code review tools

Automated code quality tools are very useful in detecting errors, bugs and code quality issues early. These code analysis tools automatically analyze your code to ensure it meets the desired quality standards and also ensure software quality. They can flag bad practices such as unoptimized code, unused variables or violations in naming conventions. Most developers or organizations use well-known tools such as SonarQube, ESLint and Checkstyle to enforce code quality checks at various stages of development.

3. Write automated tests

As coding tends to be error prone, it is crucial to test the written code and maintain its quality. Efficient use of unit tests, integration tests and functional tests confirms the code works as it is supposed to and remains intact after code changes and over time. Automated tests are especially useful in identifying bugs and regressions in code quickly so software developers or the engineering team can address them prior to the progression of the development process. The more tests you have, the more confident you can be in the quality of the code.

4. Refactor regularly

Even well-written and efficient code can become outdated or inefficient as the project evolves. Clean code can only come through proper and frequent code refactoring, which is the practice of streamlining code by eliminating redundancy and simplification of complex structures without changing the core. This step is especially important in legacy systems, where old code can create a bottleneck for further development.

Refactoring helps in making a codebase and modules more dynamic and scalable so the buildup of technical debt is avoided. When most deadlines are tight and the pressure is on the finishing scope, there may be a temptation to completely omit refactoring. However, ignoring it leads to long-term code quality problems which will be more difficult (and expensive) to fix in the future.

To ensure you’re writing and maintaining quality code, it’s important to equip yourself with the right tools. Automated code quality tools not only help catch bugs early but also ensure your code meets the necessary code quality standards. Below are some of the top tools developers rely on to maintain efficiency and readability in their projects.

• 1. SonarQube

  This widely used tool performs automatic code reviews, identifying bugs, vulnerabilities and code quality issues. It applies regular expressions to detect violations of coding standards, such as the proper use of a camel case in variable and method names. While SonarQube excels at identifying basic structural issues, it may fall short when evaluating the semantic meaning behind variable names or functions.

• 2. ESLint

  ESLint is particularly useful for JavaScript projects. It helps in identifying problematic patterns in code and enforcing coding quality practices across teams.

• 3. Checkstyle

  For Java developers, Checkstyle ensures that code adheres to predefined standards. It checks for stylistic errors and can be integrated into build processes.

• 4. GitHub Copilot

  Powered by AI, GitHub Copilot goes a step beyond traditional static code analyzers by not only offering code suggestions but also validating whether variable names, methods and classes carry meaningful semantic weight. For instance, Copilot can determine if your variable names make sense in the context of the software you’re building. This tool addresses a key shortcoming of static analyzers like SonarQube, which focuses primarily on formatting and syntax rather than the deeper meaning behind the code.

• 5. Amazon CodeGuru

  Similarly to Copilot, Amazon CodeGuru offers AI-powered insights to boost code quality and security. It provides recommendations for optimizing code performance and also checks whether naming conventions are both syntactically correct and contextually meaningful. It excels in the AWS environment and integrates well with existing development workflows.

  In addition to these tools, many leading companies that build software development platforms also create AI plugins that help with automatic quality analysis. This includes but is not limited to JetBrains AI Assistant, Microsoft Copilot, GitHub Copilot, AWS Q and many others.

Reliable, scalable and maintainable software cannot be achieved without the constant improvement and protection of code quality. If policies for the quality of code are implemented early, they will guarantee that the future efforts to maintain the application, fix its bugs or implement new features will be minimal, regardless of whether you are working alone or with a large team.

The development workflow greatly benefits from using tools for AI assistance like GitHub Copilot and Amazon CodeGuru or tools like SonarQube for the analysis of the development process. These technologies automate time-consuming checks and code quality measurement, assist in detecting possible problems with quality early and guarantee that your code is not only technically sound but also understandable and meaningful. 

In addition to encouraging better coding practices, there are a number of ways on how best practices — including regular refactoring, testing, code quality assessments and compliance with coding standards — can also help to produce better quality code. Over time, the consistent implementation of these practices leads to improved metrics for code quality, reduced incidents of bugs and increased software development efficiency.

By understanding how to assess code quality, adopting the right tools and following structured approaches, developers can significantly improve this parameter over time. You can also search for help with code audit from a reliable software development vendor.