A framework of dynamic data structures for string processing. In this paper we present DYNAMIC, an open-source C++ library implementing dynamic compressed data structures for string manipulation. Our framework includes useful tools such as searchable partial sums, succinct/gap-encoded bitvectors, and entropy/run-length compressed strings and FM indexes. We prove close-to-optimal theoretical bounds for the resources used by our structures, and show that our theoretical predictions are empirically tightly verified in practice. To conclude, we turn our attention to applications. We compare the performance of five recently-published compression algorithms implemented using DYNAMIC with those of state-of-the-art tools performing the same task. Our experiments show that algorithms making use of dynamic compressed data structures can be up to three orders of magnitude more space-efficient (albeit slower) than classical ones performing the same tasks.
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References in zbMATH (referenced in 5 articles , 1 standard article )
Showing results 1 to 5 of 5.
- Bannai, Hideo; Gagie, Travis; I, Tomohiro: Refining the (r)-index (2020)
- Bannai, Hideo; Gagie, Travis; Tomohiro, I.: Online LZ77 parsing and matching statistics with RLBWTs (2018)
- Ohno, Tatsuya; Sakai, Kensuke; Takabatake, Yoshimasa; I, Tomohiro; Sakamoto, Hiroshi: A faster implementation of online RLBWT and its application to LZ77 parsing (2018)
- Policriti, Alberto; Prezza, Nicola: LZ77 computation based on the run-length encoded BWT (2018)
- Prezza, Nicola: A framework of dynamic data structures for string processing (2017)