Approximating Approximate Pattern Matching

Authors Jan Studený, Przemysław Uznański

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Author Details

Jan Studený
  • Department of Computer Science, ETH Zürich, Switzerland
Przemysław Uznański
  • Institute of Computer Science, University of Wrocław, Poland

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Jan Studený and Przemysław Uznański. Approximating Approximate Pattern Matching. In 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 128, pp. 15:1-15:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Given a text T of length n and a pattern P of length m, the approximate pattern matching problem asks for computation of a particular distance function between P and every m-substring of T. We consider a (1 +/- epsilon) multiplicative approximation variant of this problem, for l_p distance function. In this paper, we describe two (1+epsilon)-approximate algorithms with a runtime of O~(n/epsilon) for all (constant) non-negative values of p. For constant p >= 1 we show a deterministic (1+epsilon)-approximation algorithm. Previously, such run time was known only for the case of l_1 distance, by Gawrychowski and Uznański [ICALP 2018] and only with a randomized algorithm. For constant 0 <= p <= 1 we show a randomized algorithm for the l_p, thereby providing a smooth tradeoff between algorithms of Kopelowitz and Porat [FOCS 2015, SOSA 2018] for Hamming distance (case of p=0) and of Gawrychowski and Uznański for l_1 distance.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
  • Approximate Pattern Matching
  • l_p Distance
  • l_1 Distance
  • Hamming Distance
  • Approximation Algorithms


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