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Efficient String Matching Based on a Two-Step Simulation of the Suffix Automaton

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Implementation and Application of Automata (CIAA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12803))

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Abstract

Automata play a very important role in the design of string matching algorithms as their use has always led to elegant and very efficient solutions in practice. In this paper, we present a new general approach to the exact string matching algorithm based on a non-standard efficient simulation of the suffix automaton of the pattern and give a specific efficient implementation of it. To show the effectiveness of our algorithm, we perform an extensive comparison against the most effective alternatives known in literature in terms of search speed and shift advancements. From our experimental results the new algorithm turns out to be very efficient in practical cases scaling much better when the length of the pattern increases, improving the search speed by nearly 10 times under suitable conditions.

This work has been supported by G.N.C.S., Istituto Nazionale di Alta Matematica “Francesco Severi” and by Programma Ricerca di Ateneo UNICT 2020-22 linea 2.

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Notes

  1. 1.

    We notice that the EPSM algorithm is designed for simply counting the number of matching occurrences without reporting the corresponding positions.

  2. 2.

    Source code is available at: https://github.com/ostafen/unique-factor-matcher.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Catania, Catania, Italy

    Simone Faro & Stefano Scafiti

Authors
  1. Simone Faro
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  2. Stefano Scafiti
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Correspondence to Stefano Scafiti .

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Editors and Affiliations

  1. University of Bremen, Bremen, Germany

    Sebastian Maneth

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Faro, S., Scafiti, S. (2021). Efficient String Matching Based on a Two-Step Simulation of the Suffix Automaton. In: Maneth, S. (eds) Implementation and Application of Automata. CIAA 2021. Lecture Notes in Computer Science(), vol 12803. Springer, Cham. https://doi.org/10.1007/978-3-030-79121-6_14

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  • DOI: https://doi.org/10.1007/978-3-030-79121-6_14

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  • Online ISBN: 978-3-030-79121-6

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