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A team of software testers is attempting to create an AI algorithm to assist in software testing. This particular team has gone through over 40 iterations of testing and cannot afford to spend as much time as it takes to run the full regression test suite. They are hoping to have the algorithm reduce the amount of testing required thus reducing the time needed for each testing cycle. How can an AI-based tool be expected to assist in this reduction?
Correct Answer: B
AI-based tools can significantly optimize regression test suites by analyzing historical data, past test results, associated defects, and changes made to the software. These tools prioritize and select the most relevant test cases based on previous defect patterns and frequently failing features, which helps in reducing the test execution time while maintaining effectiveness. The optimization process involves: * Prioritizing test cases:AI-based tools rank test cases based on past defect detection trends, ensuring that the most relevant tests are executed first. * Reducing redundant test cases:The tool can eliminate test cases that do not contribute significantly to defect detection, reducing overall test execution time. * Augmenting test cases:The AI can also suggest new test cases if certain features are more prone to defects. This approach has been proven to reduce regression test suite sizes by up to 50% while maintaining fault detection capabilities. * Section 11.4 - Using AI for the Optimization of Regression Test Suitesstates that AI-based tools can optimize regression test suites by analyzing past test data and defect occurrences, leading to significant reductions in test execution time. Reference from ISTQB Certified Tester AI Testing Study Guide:
