I built FixProof to verify whether AI-generated bug fixes are actually proven

A developer built FixProof, an MIT-licensed open-source tool that verifies whether AI-generated bug fixes are actually proven by their regression tests. FixProof runs the selected test against committed code before and after a fix, checks for test-integrity warnings, and issues one of four verdicts, currently supporting node:test along with GitHub Actions integration and a browser-based report viewer. The project has reached v1.0.0, and its author is seeking developers using AI-assisted coding tools to test it on real bug fixes.

AI coding tools can generate a fix and tell us the bug is solved. But there is an important question: Did the regression test actually prove the fix? That question led me to build FixProof , an MIT-licensed open-source developer tool for checking the evidence behind AI-generated bug fixes. FixProof follows a simple proof chain: Fail before → pass after → inspect test-integrity warnings → verdict It runs the selected regression test against the committed code before the fix and again against the committed code after the fix. A passing test after the change is not enough by itself. FixProof also looks for warning signs such as: The goal is to make it harder for a change to appear verified when the regression test never properly reproduced the original problem. FixProof reports one of four outcomes: FixProof v1.0 currently supports: node:test It also includes GitHub Actions integration and a browser-based report viewer. A basic verification looks like this: node bin/fixproof.mjs verify \ --repo ../my-project \ --base HEAD~1 \ --head HEAD \ --test tests/regression.test.mjs \ --output fixproof-report.json FixProof creates a report describing what happened before and after the change and any integrity warnings it found. The report can then be opened in the browser viewer. FixProof does not claim that a verified result means the entire application is bug-free. It verifies a much narrower question: Does the selected regression evidence reliably demonstrate this particular fix within the tested scope and environment? I think keeping that boundary explicit is important, especially when AI coding agents are involved. The project has now reached v1.0.0 . GitHub: https://github.com/burhanarif472-lgtm/fixproof https://github.com/burhanarif472-lgtm/fixproof Live demo: https://burhanarif472-lgtm.github.io/fixproof/ https://burhanarif472-lgtm.github.io/fixproof/ The project is open source under the MIT License. I’m now looking for developers who use AI-assisted coding tools to try FixProof on real bug fixes. I’d especially like to learn: Finding the limitations is more valuable to me right now than simply collecting stars. If you try it, I’d appreciate hearing what works, what breaks, and what you would change.