BlowChoc filters

Schmitz, Johanna Elena; Zentgraf, Jens; Rahmann, Sven

doi:10.4230/artifacts.23082

Artifact

BlowChoc filters Software

Authors Johanna Elena Schmitz , Jens Zentgraf , Sven Rahmann

Part of: Collection: Supplementary Materials
License: MIT License
Publication Date: 2025-07-15

Document Identifiers

DOI: 10.4230/artifacts.23082
URN: urn:nbn:de:0030-drops-230820

Author Details

Johanna Elena Schmitz

Saarbrücken Graduate School of Computer Science, Saarland Informatics Campus, Saarbrücken, Germany
Algorithmic Bioinformatics, Faculty of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany

Jens Zentgraf

Saarbrücken Graduate School of Computer Science, Saarland Informatics Campus, Saarbrücken, Germany
Algorithmic Bioinformatics, Faculty of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany

Sven Rahmann

Algorithmic Bioinformatics, Faculty of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany

Content

Software (Source Code): https://gitlab.com/rahmannlab/blowchoc-filters
archived version

Version/Status

Content created at: 2024-07-18
Status: Active (at the time of publication 2025-07-15)

Cite As Get BibTex

Johanna Elena Schmitz, Jens Zentgraf, Sven Rahmann. BlowChoc filters (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/artifacts.23082

Description

We provide implementations of a Bloom, Blocked Bloom and BlowChoc Filter (Blocked Bloom Filter wich Choices). We provide a Python implementation of the BlowChoc filters using the just-in-time compiler numba. Additionally, the repository contains all required workflows and scripts to reproduce the figures in the paper.

Subject Classification

Keywords

approximate membership data structure
probabilistic filter
Bloom filter
hashing

Programming Languages

Python
numba

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