AI used extremely sparingly is sometimes helpful to an experienced coder. "Multivac, generate a set of unit tests for this function." Okay, some of these are dumb, but it's easier getting started on this mess than just looking at a blank buffer. Helps get the juices flowing a bit. But man, you try to actually do anything with it, and suddenly you're lost chasing a will-o'-wisp.

[–] Ephera@lemmy.ml 14 points 19 hours ago (6 children)

I don't want to dismiss your point overall, but I see that example so often and it irks me so much.

Unit tests are your specification. So, 1) ideally you should write the specification before you implement the functionality. But also, 2) this is the one part where you really should be putting in your critical thinking to work out what the code needs to be doing.

An AI chatbot or autocomplete can aid you in putting down some of the boilerplate to have the specification automatically checked against the implementation. Or you could try to formulate the specification in plaintext and have an AI translate it into code. But an AI without knowledge of the context nor critical thinking cannot write the specification for you.

[–] merc@sh.itjust.works 2 points 6 hours ago

Tests are probably both the best and worst things to use LLMs for.

They're the best because of all the boilerplate. Unit tests tend to have so much of that, setting things up and tearing it down. You want that to be as consistent as possible so that someone looking at it immediately understands what they're seeing.

OTOH, tests are also where you figure out how to attack your code from multiple angles. You really need to understand your code to think of all the ways it could fail. LLMs don't understand anything, so I'd never trust one to come up with a good set of things to test.

load more comments (5 replies)

load more comments (9 replies)