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After AI Fixes a Failing Test, QA Must Still Verify the Fix Is Meaningful

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As AI-powered self-healing tools like mabl, Testim, and Applitools become common in software testing, a key question arises: does a passing test after an AI fix actually mean the problem was solved? QA engineers are cautioned to verify whether the repaired test still checks the same functionality and aligns with the original requirement. It is also important to determine whether the failure stemmed from a genuine UI change and whether the fix holds up across multiple subsequent runs. The concern is that AI may find an alternative path to a green result without truly addressing the underlying issue. Experts argue that the real value of AI self-healing lies not in faster fixes, but in freeing QA teams to make more informed, deliberate decisions about test validity.

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After AI Fixes a Failing Test, QA Must Still Verify the Fix Is Meaningful · ShortSingh