The correct option is A unit test that uses Copilot generated fuzz cases to feed many input variations and checks both sanitization rules and a time budget across the corpus.

This approach exercises a wide range of benign and adversarial inputs so it can verify that input handling remains safe against SQL injection attempts across many cases. It also applies a consistent performance budget to the whole corpus which helps catch pathological slowdowns and ensures acceptable runtime beyond a single representative input. Copilot can help generate diverse variations that uncover edge cases in both correctness and speed.

A unit test that measures runtime with timeit and asserts the function finishes under 800 milliseconds for representative inputs focuses on speed for a narrow sample and it does not validate defenses against injection or expose worst case inputs that may run much slower.

A unit test that asserts a sanitizer function returns a specific SQL safe string for a given user input is too narrow because it checks only one transformation and it does not measure runtime or cover the many payload patterns that matter for real security.

A unit test that benchmarks a popular external helper against the project's custom function and picks the faster result compares implementations but it does not prove that either is correct or safe and it ignores a clear time budget across varied inputs.

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