Practical Dynamic Entropy-Compressed Bitvectors with Applications

  • Joshimar CordovaEmail author
  • Gonzalo Navarro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9685)


Compressed data structures provide the same functionality as their classical counterparts while using entropy-bounded space. While they have succeeded in a wide range of static structures, which do not undergo updates, they are less mature in the dynamic case, where the theory-versus-practice gap is wider. We implement compressed dynamic bitvectors B using \(|B|H_0(B)+o(|B|)\) or \(|B|H_0(B)(1+o(1))\) bits of space, where \(H_0\) is the zero-order empirical entropy, and supporting queries and updates in \(\mathcal {O}(w)\) time on a w-bit word machine. This is the first implementation that provably achieves compressed space and is also practical, operating within microseconds. Bitvectors are the basis of most compressed data structures; we explore applications to sequences and graphs.


Query Time Adjacency List Head Cell Memory Area Wavelet Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computer Science, CeBiB — Center of Biotechnology and BioengineeringUniversity of ChileSantiagoChile

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