How can AI be utilized to enhance the accuracy of automated test result analysis?
- Ignoring test results and relying on human analysis
- Predicting expected outcomes based on historical data
- Randomly selecting test results for analysis
- Restricting analysis to predefined criteria
AI can enhance the accuracy of automated test result analysis by predicting expected outcomes based on historical data. By learning patterns from past test executions, AI algorithms can identify anomalies, deviations, and potential issues in the test results. This predictive analysis helps in quickly detecting defects, reducing false positives, and improving the overall reliability of automated testing.
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