Fully dynamic data structure for LCE queries in compressed space
Abstract
A Longest Common Extension (LCE) query on a text of length asks for the length of the longest common prefix of suffixes starting at given two positions. We show that the signature encoding of size [Mehlhorn et al., Algorithmica 17(2):183-198, 1997] of , which can be seen as a compressed representation of , has a capability to support LCE queries in time, where is the answer to the query, is the size of the Lempel-Ziv77 (LZ77) factorization of , and is an integer that can be handled in constant time under word RAM model. In compressed space, this is the fastest deterministic LCE data structure in many cases. Moreover, can be enhanced to support efficient update operations: After processing in time, we can insert/delete any (sub)string of length into/from an arbitrary position of in time, where . This yields the first fully dynamic LCE data structure. We also present efficient construction algorithms from various types of inputs: We can construct in time from uncompressed string ; in time from grammar-compressed string represented by a straight-line program of size ; and in time from LZ77-compressed string with factors. On top of the above contributions, we show several applications of our data structures which improve previous best known results on grammar-compressed string processing.
Keywords
Cite
@article{arxiv.1605.01488,
title = {Fully dynamic data structure for LCE queries in compressed space},
author = {Takaaki Nishimoto and Tomohiro I and Shunsuke Inenaga and Hideo Bannai and Masayuki Takeda},
journal= {arXiv preprint arXiv:1605.01488},
year = {2016}
}
Comments
arXiv admin note: text overlap with arXiv:1504.06954