alt Hacker NewsI see this get mentioned a lot but I still am skeptical that AI can generate tests we can trust more than any other code we know we cannot trust.
Yes tests are conceptually isolated and that helps, but I've personally seen unit tests get generated that are semantically incorrect - that is, they test the structure of the code (e.g. they can check function output types and values), but they can't know _why_ the unit tests need to be there, so the really really helpful tests never get generated. Not to mention the obvious issues with generated tests only testing is x = x, or needless redundant tests for the same thing, or them essentially testing basic features of the language.
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AI shouldn't write tests. At least not all of them. Definitely not e2e's. The tests should be guardrails to constrain agents. This way, the author of code matters less.
Which is why test generation has to be carefully guided as well, and this is something at which I've incidentally been fast. Ultimately it's a constant battle between LLM handholding and doing things yourself.
I don't even care about tests being correct as you can still verify them even when tedious. What I care is that, more often than not, the shape of the solution is not fixed. Having unit tests for those can be extremely costly as when the changes happens, you have to change all the tests.
I've been burned by this in my honeymoon period with unit testing (pretty much the reason it ended). These days, I prefer broader scope of testing, especially user-facing part. The users may be other developers or end users. I only do unit testing for tricky algorithms or math formulae.
You have to iterate on the tests, review and validate them, just like any other code, and if you generate a whole project's tests all at once the quality is abysmal, of course. I've been using a lot of old school data-driven testing techniques, where the harness is just code I review, and the data itself is e.g. json files and drives the system.
I actually have a public (AGPL) example here: https://github.com/pgdogdev/pgdog/tree/main/integration/sql - pgdog is particularly testable since it is trying for complete transparency, so you have a perfect oracle in hand via base postgresql, but it demonstrates the concept at least.