# SonarQube Projects at AI Tinkerers

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> Markdown URL: https://aitinkerers.org/technologies/sonarqube.md
> Technology record last updated: 2026-02-25T10:16:03Z
> Generated: 2026-09-22T18:41:32Z

SonarQube is the industry standard for automated code review: it scans 30+ languages to catch bugs, vulnerabilities, and technical debt before they hit production.

This platform acts as the gatekeeper in your CI/CD pipeline (Jenkins, GitHub Actions, or GitLab). It analyzes source code against 5,000+ rules to identify critical flaws like SQL injections and cross-site scripting (XSS). By enforcing Quality Gates, teams ensure that new code meets strict benchmarks for test coverage (often 80%+) and maintainability. It provides developers with immediate feedback on hotspots, helping them resolve issues in Java, C#, and JavaScript during the development cycle rather than after deployment.

- Official technology site: https://www.sonarsource.com/products/sonarqube/
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Self-healing code from Docs](https://berlin.aitinkerers.org/talks/rsvp_V3U7W4z5oaw)

The idea is basic: generate python code based on library documentation, on which the LLM hasn't been trained. But with the current state of LLMs, this turns out to be overly optimistic. So we relocate the effort of the task to the environment engineering. How can the environment, with which the agent interacts, maximally contribute to the agent's evolution and success? Fortunately, the task of code generation offers a rich feedback loop, from static code analysis tools, to run time execution logs, to code base knowledge graphs. In this talk I will make a demo of the coding assistant and provide a sneak peak into the ongoing process of enriching the environment/agent interaction for optimal agent performance.

- Event context: AI Tinkerers Berlin - November 24 — 2023-11-24 — Berlin
- Public talk page: https://berlin.aitinkerers.org/talks/rsvp_V3U7W4z5oaw

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- [Language Models](https://aitinkerers.org/technologies/language-models) ([Markdown](https://aitinkerers.org/technologies/language-models.md)) — 4 public demos
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