Re: slowly decommission bugzilla?
Mauro Carvalho Chehab <[email protected]> Mon, 2 Mar 2026 09:55:54 +0100
| Newsgroups | dev.linux.lists.ksummit |
|---|---|
| Message-ID | <[email protected]> |
On Sun, 01 Mar 2026 11:15:53 -0500 James Bottomley <[email protected]> wrote: > On Sun, 2026-03-01 at 16:35 +0100, Laurent Pinchart wrote: > > On Sun, Mar 01, 2026 at 10:23:00AM -0500, Sasha Levin wrote: > > > On Sat, Feb 28, 2026 at 03:56:11PM -0500, Steven Rostedt wrote: > > > > On Sat, 28 Feb 2026 21:28:57 +0100 (CET) > > > > Richard Weinberger <[email protected]> wrote: > > > > > > > > > Wouldn't that only work if the report is able to upload the > > > > > kernel debug info too? > > > > > > > > Yes, this would be nice if we had the help from the distros that > > > > could automate this process. > > > > > > So I've been poking at using LLMs for this. > > > > > > decode_stacktrace.sh is great when you have a debug build handy, > > > but asking a random bug reporter to obtain debuginfo, set up the > > > tooling, and run the script is quite the hurdle. > > > > > > The debuginfo problem is solvable on the server side though. Given > > > a kernel version string from the oops, an LLM can figure out which > > > distro and package version the reporter is running, pull the right > > > debuginfo (or build from the matching config/tag if no debuginfo > > > package exists), and run decode_stacktrace.sh itself. > > > > Do we really have to use non-deterministic tools that will inevitably > > produce correct-looking but otherwise useless backtraces from time to > > time, confusing developers and wasting time for everybody, when we > > can instead easily develop tools that will work in a deterministic > > fashion ? > > So "non-deterministic" is the new anti-AI phrase? I get that some > people think it's never useful, but this does seem like one of the > cases where humans can't be bothered most of the time and AI can > provide a reasonable response. > > We could even give it bonus points for building the kernel with the > revert and asking the reporter to try it (which should also be possible > if a bit expensive in terms of cloud resources). Sounds an interesting idea, but making AI write patches (or produce an output that requires a more strict format) is not something that doesn't work out of the box, if you use only LLM. I did some tests myself, writing a program meant to strings on a .po file, meant to complete a language translation(*). The only way it worked is when I used a prompt asking it to produce a "from/to" table, and then writing a function that would do the string replacements. If we want AI to produce revert patches, it is probably better to: - use a prompt for LLM to pick the original code and generate a new code to replace; - compile the code to be sure that LLM didn't break it. If it does, send back the issues to LLM - eventually repeating this step a couple of times before giving up; - run "diff" command line (or use a diff library) to produce a valid output. (*) In the end, I opted to not use it in practice, nor the produced patches, as despite LLM translation were not bad (I tested it on languages I can understand), it didn't pick right some more technical messages. It also mangled a little bit with message capitalization and whitespacing. If I had enough time to do translations myself, though, I would use it, as the core of the translations are good, but a significantly amount of them would require manual adjustments. Still, it could reduce a lot the time spent on doing translations. Thanks, Mauro