Which of the following is a problem with AI-generated test cases that are generated from the requirements?

Question

Options

• AThey are slow and will usually not be able to execute in the time allowed.
• BThey are defect prone because they are unable to detect nuances in the requirements.
• CThey make debugging more complicated because the number of steps is usually high in order to
• DThey are usually missing the expected results, so verification is difficult or must resort to only

• A
  4% (1)
• B
  11% (3)
• C
  4% (1)
• D
  82% (23)

Explanation

AI-generated test cases are often created using machine learning (ML) models or heuristic algorithms. While these can be effective in generating large numbers of test cases quickly, they often suffer from the "test oracle problem." Test Oracle Problem: A test oracle is the mechanism used to determine the expected output of a test case. AI-generated test cases often lack expected results because AI-based tools do not inherently understand what the correct output should be. Difficulty in Verification: Without expected results, verifying test cases becomes challenging. Testers must rely on heuristics, anomaly detection, or significant failures, rather than traditional pass/fail conditions.

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