### Abstract

Consider a text string of length n, a pattern string of length m, and a match vector of length n which declares each location in the text to be either a mismatch (the pattern does not occur beginning at that location in the text) or a potential match (the pattern may occur beginning at that location in the text). Some of the potential matches could be false, i.e., the pattern may not occur beginning at some location in the text declared to be a potential match. We investigate the complexity of two problems in this context, namely, checking if there is any false match, and identifying all the false matches in the match vector. We present an algorithm on the CRCW PRAM that checks if there exists any false match in O(1) time using O(n) processors. Since string matching takes Ω(log log m) time on the CRCW PRAM, checking for false matches is provably simpler than string matching. As an important application, we use this simple algorithm to convert the Karp-Rabin Monte Carlo type string matching algorithm into a Las Vegas type algorithm without asymptotic loss in complexity. We also present an efficient algorithm for identifying all the false matches and as a consequence, show that string matching algorithms take Ω(log log m) time even given the flexibility to output a few false matches. In addition, we give a sequential algorithm for checking using three heads on a 2-way deterministic finite slate automaton (DFA) in linear time and another on a 1-way DFA with a fixed number of heads.

Original language | English (US) |
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Title of host publication | Combinatorial Pattern Matching - 4th Annual Symposium, CPM 1993, Proceedings |

Editors | Zvi Galil, Maxime Crochemore , Alberto Apostolico, Alberto Apostolico, Zvi Galil, Udi Manber |

Publisher | Springer-Verlag |

Pages | 164-178 |

Number of pages | 15 |

ISBN (Print) | 9783540567646 |

State | Published - Jan 1 1993 |

Event | Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017 - Warsaw, Poland Duration: Sep 11 2017 → Sep 15 2017 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 684 LNCS |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Conference

Conference | Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017 |
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Country | Poland |

City | Warsaw |

Period | 9/11/17 → 9/15/17 |

### Fingerprint

### ASJC Scopus subject areas

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*Combinatorial Pattern Matching - 4th Annual Symposium, CPM 1993, Proceedings*(pp. 164-178). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 684 LNCS). Springer-Verlag.

**Detecting false matches in string matching algorithms.** / Muthukrishnan, Shanmugavelayutham.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Combinatorial Pattern Matching - 4th Annual Symposium, CPM 1993, Proceedings.*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 684 LNCS, Springer-Verlag, pp. 164-178, Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017, Warsaw, Poland, 9/11/17.

}

TY - GEN

T1 - Detecting false matches in string matching algorithms

AU - Muthukrishnan, Shanmugavelayutham

PY - 1993/1/1

Y1 - 1993/1/1

N2 - Consider a text string of length n, a pattern string of length m, and a match vector of length n which declares each location in the text to be either a mismatch (the pattern does not occur beginning at that location in the text) or a potential match (the pattern may occur beginning at that location in the text). Some of the potential matches could be false, i.e., the pattern may not occur beginning at some location in the text declared to be a potential match. We investigate the complexity of two problems in this context, namely, checking if there is any false match, and identifying all the false matches in the match vector. We present an algorithm on the CRCW PRAM that checks if there exists any false match in O(1) time using O(n) processors. Since string matching takes Ω(log log m) time on the CRCW PRAM, checking for false matches is provably simpler than string matching. As an important application, we use this simple algorithm to convert the Karp-Rabin Monte Carlo type string matching algorithm into a Las Vegas type algorithm without asymptotic loss in complexity. We also present an efficient algorithm for identifying all the false matches and as a consequence, show that string matching algorithms take Ω(log log m) time even given the flexibility to output a few false matches. In addition, we give a sequential algorithm for checking using three heads on a 2-way deterministic finite slate automaton (DFA) in linear time and another on a 1-way DFA with a fixed number of heads.

AB - Consider a text string of length n, a pattern string of length m, and a match vector of length n which declares each location in the text to be either a mismatch (the pattern does not occur beginning at that location in the text) or a potential match (the pattern may occur beginning at that location in the text). Some of the potential matches could be false, i.e., the pattern may not occur beginning at some location in the text declared to be a potential match. We investigate the complexity of two problems in this context, namely, checking if there is any false match, and identifying all the false matches in the match vector. We present an algorithm on the CRCW PRAM that checks if there exists any false match in O(1) time using O(n) processors. Since string matching takes Ω(log log m) time on the CRCW PRAM, checking for false matches is provably simpler than string matching. As an important application, we use this simple algorithm to convert the Karp-Rabin Monte Carlo type string matching algorithm into a Las Vegas type algorithm without asymptotic loss in complexity. We also present an efficient algorithm for identifying all the false matches and as a consequence, show that string matching algorithms take Ω(log log m) time even given the flexibility to output a few false matches. In addition, we give a sequential algorithm for checking using three heads on a 2-way deterministic finite slate automaton (DFA) in linear time and another on a 1-way DFA with a fixed number of heads.

UR - http://www.scopus.com/inward/record.url?scp=0005311094&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0005311094&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9783540567646

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 164

EP - 178

BT - Combinatorial Pattern Matching - 4th Annual Symposium, CPM 1993, Proceedings

A2 - Galil, Zvi

A2 - Crochemore , Maxime

A2 - Apostolico, Alberto

A2 - Apostolico, Alberto

A2 - Galil, Zvi

A2 - Manber, Udi

PB - Springer-Verlag

ER -