πŸ€– Day 20: Learn about AI self-healing tests and evaluate how effective they are

Hey all,

I’m going with the Option 2.

I’ve read some articles over Self Healing Tests & they seem to be pretty helpful. The pain point that it claims to resolve is maintaining the reliability of automated tests. It achieves this through:

  • Identification of broken locators
  • Alternative locator strategies
  • Suggesting alternative locators/Automatic locator updates (self-healing)

Few months back there is an update happened to our AUT and most of the locators have been changed. For our existing regression suites, to fix all these locators manually took so much time. Now, while reading these articles I’ve felt like, it would’ve been helpful if we’ve known this at that time.

But everything comes with a potential downsides, here the main concerns are:

  • False Positives
  • Integration Challenges
  • Limited Scope

I’d be open to using/exploring these tools to improve our team’s testing efficiency. Also to handle the downsides, we’d have a tester review the changes, combine with manual testing as they might not handle complex logic & get proper knowledge, implement it at smaller scale before the actual usage.

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