I know, but even regarding bug catching, there have been a LOT of bogus bug reports “discovered by AI” that could not be replicated in any way, shape or form. Granted, I’ve seen one or two articles saying that AI helped find real software bugs, but what’s the ratio there, 1:500 for useful/useless AI bug reports?
Granted, I’ve seen one or two articles saying that AI helped find real software bugs, but what’s the ratio there, 1:500 for useful/useless AI bug reports?
It’s worth distinguishing between LLM generated bug-reports submitted by randos, and developers themselves using LLMs to look for bugs in their software.
My own experience, with my own code-bases, is that the LLM I use is extremely good at finding real flaws in my code. It’ll also nitpick a lot, but it has has become better at triaging issues than it used to be, so that kind of thing is easy to ignore.
Because of that, having an LLM take a look at my code before I push it has become another QC step, along with running tests, linters, and formatters. The end result is higher quality software
I know, but even regarding bug catching, there have been a LOT of bogus bug reports “discovered by AI” that could not be replicated in any way, shape or form. Granted, I’ve seen one or two articles saying that AI helped find real software bugs, but what’s the ratio there, 1:500 for useful/useless AI bug reports?
It’s worth distinguishing between LLM generated bug-reports submitted by randos, and developers themselves using LLMs to look for bugs in their software.
My own experience, with my own code-bases, is that the LLM I use is extremely good at finding real flaws in my code. It’ll also nitpick a lot, but it has has become better at triaging issues than it used to be, so that kind of thing is easy to ignore.
Because of that, having an LLM take a look at my code before I push it has become another QC step, along with running tests, linters, and formatters. The end result is higher quality software
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