Perfect Coverage, Hidden Vulnerabilities: Why Mutation Testing Exposes AI Testing Blind Spots

AI coding assistants like Claude Code generate test suites with high coverage metrics that look correct on paper, yet routinely miss critical boundary-condition bugs that slip into production. Mutation testing fills this gap by introducing deliberate code changes to verify whether tests actually catch defects rather than merely executing code paths. As AI-generated tests increasingly ship without the boundary-value reasoning humans naturally apply, mutation testing becomes essential for developers who rely on AI assistance.