Robust Binary Search

Robust Binary Search provides a binary search implementation which is robust against errors during the search. In other words, if the comparison function sometimes returns an incorrect result, the search in this project will still converge on the correct solution.

This is adapted from the multiplicative weights algorithm in "Noisy binary search and its applications" by Karp and Kleinberg, with adjustments to make it deterministic and then extended to support directed acyclic graphs.

Usage

See AutoSearcher for binary search over a linear range and AutoCompressedDAGSearcher for binary search over a graph.

If you're looking for a git bisect replacement, see the robust-git-bisect crate which uses this library.

Performance

This code is optimized to minimize the number of tests executed (i.e. number of iterations) and not necessrily the CPU time of the search algorithm itself, so this will be slower than a plain binary search if the test is deterministic.

The linear algorithm (Searcher and AutoSearcher) takes approximately O(log N) time per iteration. The graph algorithm (CompressedDAGSearcher and AutoCompressedDAGSearcher) takes approximately O(segments) time per iteration.