[thienannguyencv]

This benchmark measures whether tests are relevant, coherent, and have good coverage. But there's a more subtle type of error: AI creates tests that look specific to PR but are actually generic patterns mapped from the training data—correct test structure, reasonable assertions, but not actually interacting with what this specific piece of code does.

How do you differentiate between ""understood the code and generated a targeted test" and "recognized this looks like an auth flow and produced a standard auth test template"? The latter might still pass your coherence/relevance metrics while missing the actual exception.