Matching statistics were introduced to solve the approximate string matching problem, which is a recurrent subroutine in bioinformatics applications. In 2010, Ohlebusch et al. [SPIRE 2010] proposed a time and space efficient algorithm for computing matching statistics which relies on some components of a compressed suffix tree - notably, the longest common prefix (LCP) array. In this paper, we show how their algorithm can be generalized from strings to Wheeler deterministic finite automata. Most importantly, we introduce a notion of LCP array for Wheeler automata, thus establishing a first clear step towards extending (compressed) suffix tree functionalities to labeled graphs.
@article{arxiv.2301.05338,
title = {Computing matching statistics on Wheeler DFAs},
author = {Alessio Conte and Nicola Cotumaccio and Travis Gagie and Giovanni Manzini and Nicola Prezza and Marinella Sciortino},
journal= {arXiv preprint arXiv:2301.05338},
year = {2023}
}