Automating Mutation Coverage with AI: Our Journey and Key Learnings

Introduces the Mutation Coverage AI Assistant, a Dev-in-the-loop system leveraging Rovo Dev CLI to automate the improvement of mutation coverage. The assistant analyzes mutation reports, recommends classes to target, writes tests aligned with project conventions, and auto-validates coverage improvements. Key learnings include the need for package-level analysis for large projects, tightening LLM instructions to avoid common mistakes (e.g., modifying implementation classes, wildcard imports, meaningless assertions), and providing detailed, mutant-specific test-writing guidelines to generate focused, high-quality tests. The post also highlights that AI cannot fix underlying design issues like bloated classes, and emphasizes the importance of collaborative prompt evolution.