[Groxx]

Probabilistic linters does seem like a fruitful realm for them, yeah. A lot of code shares strong similarities with others in small scales, thanks to stack overflow and various other "help me solve X" -> "try Y" answer pairs.

I do wonder how to reliably tell it to ignore noisy, incorrect warnings though. They're potentially sensitive to any new input / weight / random-seed changes, so it seems like literally every LLM upgrade will run the risk of ignoring existing suppressions (or you say "ignore this whole line" and miss useful warnings) due to small perturbations...