Computing Minimal Absent Words and Extended Bispecial Factors with CDAWG Space
Abstract
A string is said to be a minimal absent word (MAW) for a string if does not occur in and any proper substring of occurs in . We focus on non-trivial MAWs which are of length at least 2. Finding such non-trivial MAWs for a given string is motivated for applications in bioinformatics and data compression. Fujishige et al. [TCS 2023] proposed a data structure of size that can output the set of all MAWs for a given string of length in time, based on the directed acyclic word graph (DAWG). In this paper, we present a more space efficient data structure based on the compact DAWG (CDAWG), which can output in time with O(\mathsf{e}_\min) space, where \mathsf{e}_\min denotes the minimum of the sizes of the CDAWGs for and for its reversal . For any strings of length , it holds that \mathsf{e}_\min < 2n, and for highly repetitive strings \mathsf{e}_\min can be sublinear (up to logarithmic) in . We also show that MAWs and their generalization minimal rare words have close relationships with extended bispecial factors, via the CDAWG.
Cite
@article{arxiv.2402.18090,
title = {Computing Minimal Absent Words and Extended Bispecial Factors with CDAWG Space},
author = {Shunsuke Inenaga and Takuya Mieno and Hiroki Arimura and Mitsuru Funakoshi and Yuta Fujishige},
journal= {arXiv preprint arXiv:2402.18090},
year = {2024}
}
Comments
Accepted for IWOCA 2024