Dear Boost community, The review of the Boost.Bloom library begins on May 13th, 2025, and will run through May 22nd, 2025. Boost.Bloom is a header-only C++ library written by Joaquín M López Muñoz, providing fast and flexible Bloom filters. These are space-efficient probabilistic data structures used to test set membership with a controllable false positive rate and minimal memory footprint. The library supports a variety of configurations and hash policies and is designed to integrate well with modern C++. You can find the library here: - Repo: https://github.com/joaquintides/bloom - Documentation: https://master.bloom.cpp.al/ Bloom filters are especially useful when: - You need to test if something is not in a large dataset, and can tolerate a small false positive rate. (e.g., avoiding duplicate URL crawls in a web crawler) - You need a memory-efficient structure to represent large sets (e.g., checking for the presence of DNA subsequences across massive genomic datasets) - You want to avoid expensive lookups for items that are definitely not present (e.g., filtering nonexistent records before querying a remote database). As always, we welcome all reviews — from quick impressions to detailed analysis. Your feedback helps ensure that the library meets Boost's high standards in terms of correctness, performance, documentation, and design. If you’re interested in contributing a review, please post to the Boost mailing list during the review period. Note: All links to other parts of Boost in the Boost.Bloom documentation are currently broken, as they were written with the assumption that the library was already integrated into Boost - please do not account for those in your review. Thank you in advance for your time and insights! Best regards, Arnaud Becheler Review Manager, Boost.Bloom