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As test suites grow, maintaining automated tests and handling script breakages can become challenging, especially with frequent application updates. I've read about AI-based tools that automate test maintenance and implement self-healing capabilities, which adapt scripts to changes in the UI or functionality.

Could you share your experiences using these AI-driven solutions for automating test maintenance? Specifically, I'm curious about:

  • How effective they’ve been in reducing manual intervention for script fixes
  • Any free tools or open-source alternatives you've tried and their limitations
  • How these tools integrate with existing automation frameworks

I’d love to hear about any success stories or challenges you’ve faced while using them!

​@Ramanan 

There are numerous tools in the market with AI capabilities. Recently, I have used KANEAI by LambdaTest and the Testim tool. For handling UI changes and checking XPath failures, SelectorHub's XPath Healing feature is an excellent free option. Additionally, there are several other tools worth exploring.

  • Accuracy in Script Maintenance: AI tools like Mabl, Testim, and LambdaTest’s Smart Testing identify UI or DOM changes and dynamically adjust locators or test steps, minimizing script breakages.
  • Time-Saving: These tools drastically reduce manual intervention, especially in applications with frequent updates. For instance, Mabl's auto-healing feature allowed me to maintain large test suites without re-writing scripts for every minor UI tweak.
  • Early Issue Detection: By flagging potential breakpoints proactively, they help teams resolve issues during the CI/CD pipeline itself.

Tool recommended:

1.Healenium: An open-source library for Java-based Selenium tests that replaces broken locators with updated ones during runtime.

2.Testim.io

  • Self-healing for locators and dynamic components.
  • Adaptive learning for elements, making it robust against frequent UI updates.
  • Limitation: Requires manual integration and setup; limited community support.

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