Best code quality tools (2024) 

Coding is a fundamental aspect of software development. Since an increase in the number of complex and high-profile security software projects, coding is becoming an important part of digital transformation as well. 

But, there is a lot more to coding than just writing code and executing it. The developers must know how to write high-quality and clean code and maintain code consistency. As it not only enhances the software but also contributes to a more efficient development process. 

This is why code quality tools are here to your rescue. But, before we suggest you some code quality tools, let’s first understand what ‘Low-quality code’ is and what metrics need to be kept in mind. 

How to define ‘Low-quality code’?

In simple words, low-quality code is like a poorly-written article. 

An article that consists of grammatical errors and disorganized content which, unfortunately, fails to convey the information efficiently. Similarly, low-quality code is poorly structured and lacks adherence to coding best practices. Hence, fails to communicate logic and functions clearly. 

This is why measuring code quality is important. The code quality tools consider the qualitative and quantitative metrics for reviewing the code. 

Let’s take a look at the code metrics for code quality evolution below: 

Qualitative metrics:

Reliability

The code’s ability to perform error-free operations whenever it runs.

Maintainability:

A good-quality code is easy to maintain i.e. adding new features in less time with less effort. 

Reusability:

The same code can be used for other functions and software.

Portability:

The code is portable when it can run in different environments without any error.

Testability:

A code is of good quality when a smaller number of tests are required to verify it. 

Readability:

When the code is easily read and understood. 

Clarity:

The good-quality code should be clear enough to be easily understood by other developers. 

Documentation:

A well-documented code is when a code is both readable and maintainable i.e. Enabling other developers to understand and use it without much time and effort. 

Efficiency:

A good quality code takes less time to build and is easy to debug. 

Extensibility:

The extensible code can incorporate future changes and growth. 

Quantitative metrics:

A soft sizing algorithm that breaks down your source code into various micro functions. The result is then interpolated into a single score. 

The set of measures to evaluate the computational complexity of a software program. More the complexity, the lower the code quality.

It measures the structural complexity of the code. It is computed using the control flow graph of the program. 

5 best static code analysis tools

Static analysis code tools are software programs and scripts that analyze source or compiled code versions ensuring code quality and security. 

Below are 5 best static code analysis tools you can try:  

Typo’s automated code review tool identifies issues in your code and auto-fixes them before you merge to master. This means less time reviewing and more time for important tasks. It keeps your code error-free, making the whole process faster and smoother.

Key features:

  • Supports top 8 languages including C++ and C#
  • Understands the context of the code and fixes issues accurately
  • Optimizes code efficiently
  • Provides automated debugging with detailed explanations

A well-known static code analysis tool that enables you to write safer and cleaner code. It is an open-source package that finds different types of bugs, vulnerabilities, and issues in the code. 

  • Boasts comprehensive language support. A few of the popular ones are C#, Python, and Java. 
  • Permits integration with CI/CD pipelines with Azure DevOps server, Jenkins, and many more. 
  • Allows you to inspect the project’s code quality and security. 
  • Presents results in the form of rich reports. 

Veracode is another static analysis tool that offers fast scans and real-time feedback on your source code. It measures the software security posture of all your applications. 

  • Can be integrated with more than 40 tools and APIs. 
  • Analyse code across over 100 programming languages. Some of them are PHP, JavaScript, and SQL. 
  • Secure your software without sacrificing speed. 
  • Allows you to easily track the analyses. 

Another great offering among static analysis tools that helps you check our code quality. It blocks merges of pull requests based on your quality rules and helps prevent critical issues from affecting your product. 

  • Supported by more than 40+ languages. A few of them are C++, Go, and CoffeeScript. 
  • Lets you identify which codes are being covered by your test suite.
  • Provides suggestions for fixes. 
  • Allows customization of analysis with hundreds of rules available. 

A well-known static analysis tool that focuses on managing and monitoring the quality of software projects. It enables you to automatically prioritize problematic snippets in the code and provide clear visualizations. 

  • Supported by various popular programming languages. A few of them are Objective-C, Solidity, and C. 
  • Monitoring options include Quality checkpoints, Customer KPIs, and Custom quality checkpoints. 
  • Multi-vector diagnostic technology that helps in analyzing code. 
  • Helps in transparently managing and improving software quality.  

PVS Studio is best known for detecting bugs and security weaknesses. It offers a digital reference guide for all analytic rules and analysis codes for errors, dead snippets, typos, and redundancy. 

  • Monitors code quality for a variety of languages. A few of them are Visual Studio, C++, and C#. 
  • The analysis report is available in various formats. HTML, XML, and TeamCity to name a few. 
  • Can be easily integrated with various products. It includes Jenkins, SonarQube, Rider, and many more. 
  • Allows simple navigation through the code’s warnings. 

5 best dynamic code analysis tools

Dynamic code analysis tools enable you to analyze and test your applications during execution against possible vulnerabilities. 

Choosing what tools fit your requirements could be a bit tricky. As these tools are language-specific and case-specific. You can pick the right tool from an open-source repository by Github based on your current situation. 

However, we have picked 5 popular dynamic code analysis tools that you can take a look at: 

A real-time code coverage tool that provides insights for penetration testing activities. 

  • Currently supports Java programs up to Java 11, and .NET Framework programs for CLR versions 2 and 4.
  • Presents coverage information visually; making it easy to understand which part of an application is covered and how much. 
  • Automatically detects coverage information while the tests are being conducted. 

A vulnerability scanner that checks whether the code follows best practices in security, performance, and reliability.  

  • Specifically designed for Laravel PHP applications that combine SAST, DAST, IAST, and configuration analysis techniques to detect vulnerabilities.
  • Helps in detecting issues in the earlier stages. 
  • Presents issues with all information and documentation links required to resolve it. 

An interactive tool that analyses un-instrumented ELF core files for leaks, memory growth, and corruption.

  • Used in automation to catch leaks before they are committed. 
  • Currently supports only glibc malloc.
  • Supplements a debugger by giving the status of various memory locations.

A framework for dynamic analysis of WebAssembly binaries. 

  • Built on binary instrumentation. 
  • Offers an easy-to-use, high-level API that allows the implementation of heavyweight dynamic analyses that can monitor all low-level behaviour.

An instrumental framework that automatically detects many memory management and threading bugs. 

  • Helps in building dynamic analysis tools for C/C++ programs.
  • Runs on UNIX systems such as Linux. 
  • Runs the binary on a CPU emulator with the appropriate
  • instrumentation for the selected analysis. 

5 best peer code review tools

Although static and dynamic code analysis tools are effective, they won’t catch everything. Since they aren’t aware of the business practices and functionality you are trying to implement. 

This is when you need another developer from your organization. And this is possible with the peer code review tools. They not only help in making better code but better teams as well. 

A few of the questions that another developer considers are: 

    • Can I find any obvious logic errors in the code? 
    • Are all cases fully implemented based on the current requirements
    • Are the new automated tests enough for the new code? Or do the existing ones need to be rewritten to account for changes in the code
    • Does the new code abide by prevailing style guidelines?

 Below are 5 best peer code review tools that you can use: 

A peer code and document review tool that enables a team to collaborate and produce high-quality code and documents. It includes a customizable workflow that makes it easy to fit seamlessly into pre-existing work processes.

  • Supports various version control systems. A few of them are Git, TFS, and CVS. 
  • Integrates with well-known project management tools and IDEs. It includes Jira, Visual Studio, and Eclipse. 
  • Analyzes team’s review process with defect metrics, custom fields, and reports.
  • Allows you to collaborate with the team on software artifacts and documents.

A standalone code review tool that allows developers to review, discuss and track pull requests in one place. Review Board is an open-source tool that lets you conduct document reviews and can be hosted on the server. 

  • Can be installed on local machines or subscribed to the cloud-based version. 
  • Supports various well-known repositories. Such as Git, Azure DevOps, and Subversion. 
  • Let you perform both pre-commit and post-commit code reviews based on your requirements.
  • Allows you to automate code reviews with the help of a review bot. 

A behavioral code analysis AI tool that uses machine learning algorithms to help find code issues in the early stages and fix them before they cause obstacles. It also helps developers in managing technical debt,  sound architectural decisions and improve efficiency. 

  • Available in two forms: A cloud-based solution and an on-premise solution.
  • Work with any Git hosting. 
  • Support for building pipelines including Jenkins. 
  • Offers a goal-oriented workflow for planning improvements. 

A lightweight code review software by Atlassian that enables the review of codes, sharing of knowledge, discussing changes, and detecting bugs across different version control systems. It allows developers to create pre-commit reviews from IntelliJ IDEA by using the Atlassian IDE Connector. 

  • Seamlessly integrate with other Atlassian products. It includes Confluence, Jira, and Bitbucket. 
  • Supported by various version control systems. Such as SVN, Git, and Mercurial. 
  • Shows how much time the reviewers took reviewing your codes.
  • Presents real-time personalized notifications and review reminders.

An open-source web-based code review tool by Google for projects with large repositories. It has Git-enabled SSH and HTTP servers that are compatible with all Git clients. 

  • Acts like a Git Server and can be deployed on a public or private cloud.
  • It allows you to track bugs and review code in one place. 
  • Manages workflows with deeply integrated and delegatable access controls. 
  • Include a simple voting system to approve or reject code changes.

How do Typo help in reviewing the quality of code?

Without sounding boastful, our motivation for creating Typo was to enhance our code review process. With Typo, you have the ability to monitor crucial code review metrics, such as review duration and comprehensiveness. Additionally, it allows you to configure notifications that alert you when a code change is merged without a review or if a review has been unintentionally overlooked. There are three major metrics it tracks – 

  1. Average commits after PR raised – Average number of commits after the PRs are raised
  2. PRs merged without review – Total number of PRs merged without review
  3. Bugs rate – Average number of issues raised against a story point/tasks done

Enhancing development processes goes beyond just increasing speed and quality; it brings predictability to your throughput. By leveraging Typo, you can achieve better performance and planning, ensuring consistent alignment throughout your organization.

To witness the transformative power of Typo firsthand, let’s schedule a demo. Get in touch, and let’s embark on a journey toward improved productivity together.