Code is like f(x)=ax+b. You test would be a list of (x,y) tuple. You don’t verify the correctness of your points because they come from some source that you hold as true. What you want is the generic solution (the theory) proposed by the formula. And your test would be just a small set of points, mostly to ensure that no one has changed the a and b parameters. But if you have a finite number of points, The AI is more likely to give you a complicated spline formula than the simple formula above. Unless the tokens in the prompts push it to the right domain space. (Usually meaning that the problem is solved already)

Real code has more dimensionality than the above example. Experts have the right keywords, but even then that’s a whole of dice. And coming up with enough sample test cases is more arduous than writing the implementation.

Unless there’s no real solution (dimensionality is high), but we have a lot of tests data with a lower dimensionality than the problem. This used to be called machine learning and we have metrics like accuracy for it.