Okay this is really fun and mathematically satisfying. Could even be useful for tough bugs that are technically deterministic, but you might not have precise reproduction steps.
Does it support running a test multiple times to get a probability for a single commit instead of just pass/fail? I guess you’d also need to take into account the number of trials to update the Beta properly.
IIUC the way you'd do that right now is just repeatedly recording the individual observations on a single commit, which effectively gives it a probability + the number of trials to do the Beta update. I don't yet have a CLI entrypoint to record a batch observation of (probability, num_trials), but it would be easy to add one
But ofc part of the magic is that git_bayesect's commit selection tells you how to be maximally sample efficient, so you'd only want to do a batch record if your test has high constant overhead
git bisect works great for tracking down regressions, but relies on the bug presenting deterministically. But what if the bug is non-deterministic? Or worse, your behaviour was always non-deterministic, but something has changed, e.g. your tests went from somewhat flaky to very flaky.
Okay this is really fun and mathematically satisfying. Could even be useful for tough bugs that are technically deterministic, but you might not have precise reproduction steps.
Does it support running a test multiple times to get a probability for a single commit instead of just pass/fail? I guess you’d also need to take into account the number of trials to update the Beta properly.
Yay, I had fun with it too!
IIUC the way you'd do that right now is just repeatedly recording the individual observations on a single commit, which effectively gives it a probability + the number of trials to do the Beta update. I don't yet have a CLI entrypoint to record a batch observation of (probability, num_trials), but it would be easy to add one
But ofc part of the magic is that git_bayesect's commit selection tells you how to be maximally sample efficient, so you'd only want to do a batch record if your test has high constant overhead
git bisect works great for tracking down regressions, but relies on the bug presenting deterministically. But what if the bug is non-deterministic? Or worse, your behaviour was always non-deterministic, but something has changed, e.g. your tests went from somewhat flaky to very flaky.
In addition to the repo linked in the title, I also wrote up a little bit of the math behind it here: https://hauntsaninja.github.io/git_bayesect.html