Below 1k Sonar Issues
2026-01-13 – Karsten Thoms
Static analysis findings drop below 1,000 issues!
Today, we’re thrilled to announce a significant milestone for the Operaton project: our static code analysis findings have dropped below 1,000 issues! This achievement reflects our ongoing commitment to code quality, maintainability, and overall project health.
A Commitment To Quality
Over the past months, our development team has been diligently working to address technical debt and improve the codebase. By leveraging tools like SonarQube, we’ve been able to identify areas for improvement and systematically tackle them.
When SonarQube was first introduced to the Operaton project, we had over 16,000 issues to address. Now, we have adressed ~95% of them.
Our mission was clear: reduce complexity, eliminate code smells, and enhance the overall quality of our BPMN engine.
Why This Matters
Reducing static analysis findings is more than just a numbers game. It directly impacts:
- Maintainability: A cleaner codebase is easier to understand, modify, and extend. This means faster development cycles and reduced risk of introducing bugs.
- Reliability: Addressing code smells and potential bugs leads to a more stable and reliable BPMN engine, which is crucial for mission-critical applications.
- Community Confidence: As an open-source project, we rely on our community of contributors and users. A high-quality codebase fosters trust and encourages more developers to get involved.
- Future Growth: A solid foundation allows us to innovate and add new features more effectively, ensuring that Operaton remains a leading choice for BPMN process automation.
How We Achieved This
Our team continously monitors the codebase using SonarQube, and resolve whatever we can.
A large portion of findings have been resolvable using OpenRefactory automated refactorings.
But beyond this, we had to tackle each of the remaining issues manually, which required careful analysis and thoughtful refactoring.
AI tools, especially GitHub Copilot, have been a great help in this process, assisting our developers in crafting cleaner, more efficient code.
Furthermore, resolving static analysis findings are a low hanging fruit for new contributors to get familiar with the codebase and contribute meaningfully. We have received refactorings from multiple first-time contributors, which has been a great help.
How You Can Help
The remaining issues are more complex and will require deeper analysis and refactoring. We invite our community members to join us in this effort. If you’re interested in contributing, here are a few ways you can help:
- Review the SonarQube Dashboard: Familiarize yourself with the current findings and identify areas where you can contribute
- Pick an Issue: Choose an issue that interests you and start working on a solution
- Submit a Pull Request: Share your improvements with the community by submitting a pull request