• DOI:10.1137/1.9781611975031.96
• Corpus ID: 10221564

Optimal-Time Text Indexing in BWT-runs Bounded Space

@inproceedings{Gagie2017OptimalTimeTI,
  title={Optimal-Time Text Indexing in BWT-runs Bounded Space},
  author={Travis Gagie and Gonzalo Navarro and Nicola Prezza},
  booktitle={ACM-SIAM Symposium on Discrete Algorithms},
  year={2017}
}

• T. Gagie, G. Navarro, N. Prezza
• Published in
  ACM-SIAM Symposium on…
  29 May 2017
• Computer Science

Indexing highly repetitive texts --- such as genomic databases, software repositories and versioned text collections --- has become an important problem since the turn of the millennium. A relevant compressibility measure for repetitive texts is $r$, the number of runs in their Burrows-Wheeler Transform (BWT). One of the earliest indexes for repetitive collections, the Run-Length FM-index, used $O(r)$ space and was able to efficiently count the number of occurrences of a pattern of length $m$ in the text (in loglogarithmic time per pattern symbol, with current techniques). However, it was unable to locate the positions of those occurrences efficiently within a space bounded in terms of $r$. Since then, a number of other indexes with space bounded by other measures of repetitiveness --- the number of phrases in the Lempel-Ziv parse, the size of the smallest grammar generating the text, the size of the smallest automaton recognizing the text factors --- have been proposed for efficiently locating, but not directly counting, the occurrences of a pattern. In this paper we close this long-standing problem, showing how to extend the Run-Length FM-index so that it can locate the $occ$ occurrences efficiently within $O(r)$ space (in loglogarithmic time each), and reaching optimal time $O(m+occ)$ within $O(r\log(n/r))$ space, on a RAM machine of $w=\Omega(\log n)$ bits. Within $O(r\log (n/r))$ space, our index can also count in optimal time $O(m)$. Raising the space to $O(r w\log_\sigma(n/r))$, we support count and locate in $O(m\log(\sigma)/w)$ and $O(m\log(\sigma)/w+occ)$ time, which is optimal in the packed setting and had not been obtained before in compressed space. We also describe a structure using $O(r\log(n/r))$ space that replaces the text and extracts any text substring of length $\ell$ in almost-optimal time $O(\log(n/r)+\ell\log(\sigma)/w)$. (...continues...)