Self Healing UI Tests in Practice

[bibils]

Over the past few months, our UI automation has become a constant source of interruptions. Even small interface changes like renamed buttons or updated components seem to break tests that previously worked fine. The user flows themselves still behave correctly, but the test suite reacts as if something critical failed. This leads to a lot of manual fixes that feel repetitive and not very valuable. What makes it harder is that the product evolves quickly, so these changes happen often. We want the tests to reflect real user behavior instead of pixel-level details. I am wondering how teams reduce this maintenance burden without ignoring important UI regressions.

[kossia]

Something that helped us was learning more about how AI-assisted self-healing can be applied carefully. I found a clear explanation on https://axis-intelligence.com/artificial-intelligence-test-automation/ that describes how multiple signals like text, structure, and position can be used instead of a single fragile selector. What I appreciated is that it also talks about limits, especially for regulated or ambiguous screens. The idea of logging every healed change and reviewing patterns made it feel more controlled. It allowed UI tests to stay focused on real journeys while still being auditable. That balance reduced noise without hiding meaningful issues.

[siiaenko]

UI automation maintenance seems to be a shared challenge as products change faster. Tests that constantly fail for superficial reasons quickly lose trust. Approaches that keep behavior checks stable while tracking changes transparently sound reasonable. It shows that the goal is not fewer checks, but better signals. Discussions like this highlight how test automation needs to adapt alongside design and development workflows. Stability and visibility appear to matter just as much as coverage.

[sodoxat]

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