LLMs have helped me here the most. Adding copious detailed logging across the app on demand, then inspecting the logs to figure out the bug and even how to reproduce it.

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bluGill 3 hours ago | parent | next [-]

I did that once: logging ended up taking 80% of the CPU leaving not enough overhead for everything else the system should do. Now I am more careful to figure out what is worth logging at all, and also to make sure disabled logs are quickly bypassed.

	▲	dylan604 18 minutes ago \| parent [-]
		we've gotten into adding verbosity levels in logging where each logged event comes with an assigned level that only makes it to the log if it matches the requested log level. there are times when a full verbose output is just too damn much for day-to-day debugging, but is helpful when debugging the one feature. i used to think options like -vvv or -loglevel panic were just someone being funny, but they do work when necessary. -loglevel sane, -loglevel unsane, -loglevel insane would by my take but am aware that most people would roll their eyes so we're lame using ERROR, WARNING, INFO, VERBOSE

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ChrisMarshallNY 12 hours ago | parent | prev [-]

Yes. I often just copy the whole core dump, and feed it into the prompt.

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criddell 3 hours ago | parent | next [-]

This is something that I've been trying to improve at. I work on a Windows application and so I get crash dumps that I open with WinDbg and then I usually start looking for exceptions.

Is this something an LLM could help with? What exactly do you mean when you say you feed a dump to the prompt?

	▲	ChrisMarshallNY 2 hours ago \| parent [-]
		I literally copy the whole stack dump from the log, and paste it into the LLM (I find that ChatGPT does a better job than Claude), along with something along the lines of: > I am getting occasional crashes on my iOS 17 or above UIKit program. Given the following stack trace, what problem do think it might be? I will attach the source file, if I think I know the general area, along with any symptoms and steps to reproduce. One of the nice things about an LLM, is that it's difficult to overwhelm with too much information (unlike people). It will usually respond with a fairly detailed analysis. Usually, it has some good ideas to use as starting points. I don't think "I have a bug. Please fix it." would work, though. It's likely to try, but caveat emptor.

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Lionga 11 hours ago | parent | prev [-]

And this kids is how one bug got fixed and two more were created

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ChrisMarshallNY 8 hours ago | parent [-]

Nope.

Good result == LLM + Experience.

The LLM just reduces the overhead.

That’s really what every “new paradigm” has ever done.

	▲	enraged_camel 3 hours ago \| parent [-]
		Also, robust test coverage helps prevent regressions.