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arXiv · 2301.05338

Computing matching statistics on Wheeler DFAs

Alessio Conte·Nicola Cotumaccio·Travis Gagie·Giovanni Manzini·Nicola Prezza·Marinella Sciortino
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Abstract

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.

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Alessio Conte, Nicola Cotumaccio, Travis Gagie, Giovanni Manzini, Nicola Prezza, Marinella Sciortino. 2023-01-13. Computing matching statistics on Wheeler DFAs. https://arxiv.org/abs/2301.05338

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