What are the best code review tools for ensuring code quality and reducing bugs?

GitHub: GitHub offers built-in code review features that allow developers to create pull requests, comment on code changes, and collaborate on improving code quality. It also integrates with various continuous integration (CI) tools for automated testing. GitLab: GitLab provides similar code review capabilities to GitHub, including merge requests, inline code comments, and integration with CI/CD pipelines for automated testing and deployment. Bitbucket: Bitbucket, another popular Git repository management tool, offers code review features such as pull requests, inline commenting, and integration with CI/CD tools for automated testing.

SonarQube, no doubt. Not only as linter, it's the best full review tool I ever used. Community edition most of the times does the job. There is a docker image as well, to fastly deploy and try the service.

GitHub: GitHub offers built-in code review features that allow developers to create pull requests, comment on code changes, and collaborate on improving code quality. It also integrates with various continuous integration (CI) tools for automated testing. GitLab: GitLab provides similar code review capabilities to GitHub, including merge requests, inline code comments, and integration with CI/CD pipelines for automated testing and deployment. Bitbucket: Bitbucket, another popular Git repository management tool, offers code review features such as pull requests, inline commenting, and integration with CI/CD tools for automated testing.

Linters are nowadays no longer limited to just code, take into account to track also configuration file types like XML, YAML, JSON and documentation linters for Markdown or your chosen documentation formats.

GitHub: Easy reviews within the platform (if you already use GitHub). GitLab: Similar to GitHub, ideal if you use GitLab for development. Review Board: Open-source and flexible, supports various version control systems. Codacy: Automated quality checks, catches bugs early, enforces style. Gerrit: Popular for open-source, strict review process for high quality. Choosing a Tool Integration: Does it work with your existing systems? Features: How deep an analysis do you need? Cost/Customization: Do you prefer open-source or a commercial solution?

GitHub provides built-in code review features, including pull requests and inline commenting. Crucible is another tool, developed by Atlassian, which offers code review capabilities integrated with other Atlassian products like JIRA.

Counting lines of code (LOC) should not be your KPI or main code metric to track, but it helps to visualize the evolution of the codebase. Get some multi-language reports, like pygount, scc, tokei and see what works for the project, take into account the report generation for your chosen CI and report visualization landscape. Tools for complexity analysis should be able to calculate at least McCabe (cyclometric) complexity and Halstead volume. More advanced tools can also analyze important code-to-documentation metrics.

Here a well-configured framework like pre-commit can help to avoid problematic check-ins and to prevent basic bugs, untested or unlinted code and configuration to enter the project′s repository. With pre-commit, my team was able to reduce the time waiting for failed CI runs, add protection against configuration changes due to XML, YAML and JSON linters and enforce file name conventions.

Team co-authoring, under fast feedback loop (in the order or minutes or even less) is more than probably the best way to mitigate bugs while improving both knowlege and architecture through an evolutionary design. This development approach is known as ensemble programming or software teaming.

I believe that, more than tools, manual code review is the most important. A rather slow (but rewarding) approach is to make a weekly pair of two programmers, and each one would explain their latest code changes to the other. This way, not only does every team member gain other team members' perspective, you also make sure they understand their own code better by explaining it to someone else. This is very effective in catching sneaky bugs, logical flaws, design errors etc.