Testomat.io’s AI Failure Clusterization is an innovative feature designed to enhance the efficiency of your testing process by intelligently analyzing and grouping automated test failures.
Here’s how AI Failure Clusterization works
- Automated failure Analysis. The AI system scans your test execution logs to detect patterns among failed tests.
- Intelligent grouping. Similar test failures are clustered together, allowing you to quickly identify recurring issues.
- Root cause insights. By highlighting patterns in failures, the system provides insights into potential root causes, reducing investigation time.
- Enhanced debugging. With a clear understanding of failure patterns, debugging becomes more efficient, enabling faster resolution of issues.
Benefits of AI Failure Clusterization
- Faster debugging and issue resolution. AI Failure Clusterization automatically groups similar test failures, focusing testers and developers to quickly identify patterns and reduce the time spent analyzing root cases.
- Optimized test maintenance. Improves test suite stability by identifying risky tests that require attention.
- Eliminates manual efforts. QAs can easily navigate by failure clusters instead of sorting and categorizing test failures manually.
- Speeds up the feedback loop by allowing QA teams to focus on resolving grouped failures instead of analyzing them one by one.
- Enhances collaboration between testers and developers by providing structured failure insights.
- Improved test execution insights. AI-driven clustering highlights recurring failures, helping teams prioritize critical defects, and spot flaky tests, infrastructure issues, or code regressions.
- Better decision-making. AI-powered insights offer a clearer view of failure trends and recurring issues over multiple test runs. Enables teams to take proactive measures to improve software quality.
This feature is currently in its experimental phase, and user feedback is highly encouraged to refine its accuracy and usability.
