Constrained Longest Common Subsequence Computing Algorithms in Practice

Authors

  • Sebastian Deorowicz
  • Joanna Obstój

Keywords:

Longerst common subsequence, constrained longest common subsdequence, sparse dynamic programming, string matching, sequence alignment

Abstract

The problem of finding a constrained longest common subsequence (CLCS) for the sequences A and B with respect to sequence P was introduced recently. Its goal is to find a longest subsequence C of A and B such that P is a subsequence of C. There are several algorithms solving the CLCS problem, but there is no real experimental comparison of them. The paper has two aims. Firstly, we propose an improvement to the algorithms by Chin et al. and Deorowicz based on an entry-exit points technique by He and Arslan. Secondly, we compare experimentally the existing algorithms for solving the CLCS problem.

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Author Biographies

Sebastian Deorowicz

Institute of Informatics
Silesian University of Technology
Akademicka 16
44-100 Gliwice, Poland

Joanna Obstój

Goldman Sachs International
Peterborough Court
133 Fleet Street
London EC4A 2BB, England, United Kingdom

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Published

2012-01-26

How to Cite

Deorowicz, S., & Obstój, J. (2012). Constrained Longest Common Subsequence Computing Algorithms in Practice. Computing and Informatics, 29(3), 427–445. Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/92