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There is actually a bayesian version which I wrote: https://github.com/ealdwulf/bbchop

Basically it calculates the commit to test at each step which gains the most information, under some trivial assumptions. The calculation is O(N) in the number of commits if you have a linear history, but it requires prefix-sum which is not O(N) on a DAG so it could be expensive if your history is complex.

Never got round to integrating it into git though.




That's a cool idea. Would also be interesting to consider the size of the commit - a single 100-line change is probably more likely to introduce a bug than 10 10-line changes.


The commit that caused OP's bug changed two lines.

https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/lin...


You haven't met the developers at my last company.


Hidden gem! Thanks!




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