Speeding-up Hirschberg and Hunt-Szymanski LCS Algorithms

Authors:
Maxime Crochemore;Costas S. Iliopoulous;Yoan J. Pinzon
Affiliations:
Institut Gaspard-Monge, Université de Marne-la-Vallée, F-77454 Marne-la-Vallée CEDEX 2, France;Department of Computer Science, King's College London, London WC2R 2LS, UK;Department of Computer Science, King's College London, London WC2R 2LS, UK
Venue:
Fundamenta Informaticae - Computing Patterns in Strings
Year:
2003

Citing 12
Cited 0

Improving the worst-case performance of the Hunt-Szymanski strategy for the longest common subsequence of two strings

Information Processing Letters
A new approach to text searching

Communications of the ACM
Fast text searching: allowing errors

Communications of the ACM
A fast bit-vector algorithm for approximate string matching based on dynamic programming

Journal of the ACM (JACM)
The String-to-String Correction Problem

Journal of the ACM (JACM)
Algorithms for the Longest Common Subsequence Problem

Journal of the ACM (JACM)
A fast algorithm for computing longest common subsequences

Communications of the ACM
A linear space algorithm for computing maximal common subsequences

Communications of the ACM
A fast and practical bit-vector algorithm for the longest common subsequence problem

Information Processing Letters
Longest Common Subsequences

MFCS '94 Proceedings of the 19th International Symposium on Mathematical Foundations of Computer Science 1994
A Faster Algorithm for Approximate String Matching

CPM '96 Proceedings of the 7th Annual Symposium on Combinatorial Pattern Matching
A Bit-Parallel Approach to Suffix Automata: Fast Extended String Matching

CPM '98 Proceedings of the 9th Annual Symposium on Combinatorial Pattern Matching

Quantified Score

Hi-index	0.00

Visualization

Abstract

Two algorithms are presented that solve the problem of recovering the longest common subsequence of two strings. The first algorithm is an improvement of Hirschberg's divide-and-conquer algorithm. The second algorithm is an improvement of Hunt-Szymanski algorithm based on an efficient computation of all dominant match points. These two algorithms use bit-vector operations and are shown to work very efficiently in practice.