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When AI Fixes a Test, How Do We Know It Fixed the Right Thing?

A developer exploring AI-assisted testing through X360 AI Tech highlights a key concern: when AI self-heals a broken test, a passing result does not guarantee the fix targeted the correct element. The developer argues that QA review remains essential to ensure the repair preserves the test's original purpose, distinguishing between a test that merely passes and one that is correctly fixed.

read1 min views1 publishedSep 1, 2026

While exploring AI-assisted testing, I started thinking more about what actually happens when a test breaks. Tools like mabl, Testim, and Functionize are approaching self-healing in different ways, and I can see why it’s becoming useful as test suites get bigger. But I keep coming back to one thing: just because a healed test passes again, it doesn’t always mean it was fixed correctly. If a locator breaks and AI finds another element that makes the test pass, we still need to know whether it’s actually the element the test was meant to use.

While exploring these ideas through X360 AI Tech, I’ve also been looking at how much context is needed for a test change to actually make sense. For me, it’s not just about finding something that works again, but making sure the fix still supports the original purpose of the test. When that isn’t clear, I think QA review is still important. There’s a big difference between “the test passed again” and “the test passed again, and we know it was fixed correctly.” I think that difference becomes more important as test suites grow.

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