![]() ![]() They’re often consulted with the customer before the implementation starts, or after making the decision to use the static code analysis. The usual setup for SonarQube in CI/CD pipeline uses quality gates with set threshold values for selected metrics. However, if they’re used as an absolute indicator of the code quality, or even worse - as a KPI - it can have a negative effect on the entire project. As it usually is with any kind of metrics, if used and interpreted correctly, they provide the team with helpful information about the current condition of the code base. Moreover, it even tries to estimate the technical debt, assuming the time and effort required to fix all the maintainability issues. It also produces a lot of code metrics such as complexity, duplications, all kinds of issues, as well as test coverage. ![]() It highlights the problematic sections, provides clear explanations, and even proposes exemplary solutions based on similar cases. SonarQube is a great tool that can help our team with writing better code. It allowed us to maximise the potential of the Sonar suite, without making our developers hate it with a passion. So after a few lessons learned, we established some handy guidelines for effective and stress-free usage of these tools. But is it enough to just implement those tools, set up a few quality gates and strictly stick to the results of the analysis to then enforce our team to blindly “fix” their code? In our experience - it’s not. We decided on the Sonar suite (SonarQube, SonarLint and SonarScanner). It fits our practices and is easily incorporated into our CI/CD pipelines. At Objectivity, we use a tool that offers this feature along with an extensive rule base. ![]() You can achieve that by using static code analysis, which as the name suggests, doesn’t need to run the code in order to process it. One of the recommended approaches, which is the one we practise at Objectivity, is to mitigate those issues with keeping our codebase clean and free of design and security issues. They can then manifest themselves long after the deployment. However, due to the complexity of contemporary software, some vulnerabilities stay undiscovered even after extensive testing. Most of the issues regarding security, performance and extensibility are detected during the implementation process or later during the code review, where we depend entirely on the experience of our developers. Because of that, keeping it clean, fine-tuned and free of potential vulnerabilities is essential. Introducing the DevOps tools and mindset makes it possible to improve the general quality of the solution and decrease its delivery time.īut even with the most sophisticated approach, it’s important to remember that the code always is the foundation of the software. Quality control is an indispensable part of the process-software should constantly be validated, verified, and tested. It’s also ensuring that you provide the right solution, both in terms of the overall quality and business requirements. Sonarqube also provides support for 27 different languages, including C, C++, Java, Javascript, PHP, GO, Python, and much more.SonarQube also provides Ci/CD integration, and gives feedback during code review with branch analysis and pull request decoration.An efficient software delivery is more than just shipping any solution to the client as fast as possible. Sonarqube also ensures code reliability, Application security, and reduces technical debt by making your code base clean and maintainable. The software will analyze source code from different aspects and drills down the code layer by layer, moving module level down to the class level, with each level producing metric values and statistics that should reveal problematic areas in the source code that needs improvement. This provides users with a rich searchable history of the code to analyze where the code is messing up and determine whether or not it is styling issues, code defeats, code duplication, lack of test coverage, or excessively complex code. Everything from minor styling choices, to design errors are inspected and evaluated by SonarQube. It combines static and dynamic analysis tools and enables quality to be measured continually over time. SonarQube is a Code Quality Assurance tool that collects and analyzes source code, and provides reports for the code quality of your project.
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