Benchmarking a Bug Scanner

3 days ago

Building a bug scanner that prioritizes important bugs over the many low-impact ones in complex codebases.
Quantifying bug importance by comparing Detail's findings against code review bots using an LLM judge and ranking system.
Detail's bug reports were found to be significantly more important than those from code review bots, with a high signal-to-noise ratio.
Human or agent validation showed an 82.9% correctness rate for Detail's findings in recent months.
Example provided: Detail found a security vulnerability in PostHog where private sandbox environment secrets were accessible to other team members.
Tests comparing Claude Code's ability to find important bugs showed it struggled compared to Detail's targeted scanning approach.

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