I don’t know about that, but there was an article on TheRegister, a year or so ago perhaps, on some company which was using LLM’s not for generating code, but for auditing code, to flag back-doors, etc, & the guy from the company told the Reg that the stuff the LLM they were using was flagging, was problematic ( like copying user-credentials to some specific server on the internet… )
There are a couple of code-specific LLM’s, & systematically using all of them to audit every project that one is reliant-on, & then checking what they flagged, to see if that is serious or just a mistake ( by LLM or by a coder ), that might increase the discovery-of-problems enough to make it very worth our world’s time/effort.
From what I’ve read about LLM’s, though, you’d have to have problems divided into specific kinds, & you’d have to have examples of that specific problem in a few different languages, to show the LLM, as examples, before you could rely on their finding that-problem in a code-base…
Keep the question small, precise, specific, provide examples, & tell it to ask questions about anything it isn’t clear about before answering, so you aren’t relying on it answering some question you didn’t mean…
IF it removes backdoors, & other malware, then I don’t care if it’s human or derivative: results matter, right?
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