The best answer is C. Utilize a diverse set of test cases . PMI-CPMAI’s model evaluation domain focuses on building comprehensive evaluation plans and formulating appropriate evaluation questions and criteria. Validation is not treated as a one-time technical check, but as a structured process designed to test model behavior across a range of relevant conditions, edge cases, and data contexts. Using a diverse set of test cases is the best way to assess whether predictions are accurate, robust, and dependable enough for a public-sector policy setting.

Option A is useful for software quality but does not validate predictive performance. Option B is weaker because a single validation exercise can miss important failure modes, bias, or context-specific weaknesses. Option D supports engineering discipline, but continuous integration testing focuses more on code and deployment workflow than on validating model prediction quality itself. PMI’s CPMAI framework emphasizes comprehensive evaluation design, iteration, and addressing performance issues such as drift and changing conditions. That makes broad and varied test coverage the most PMI-aligned approach to model validation. In practical terms, diverse test cases provide stronger evidence that the model will generalize beyond a narrow sample and support trustworthy decision-making.