### 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 a false match in O(1) time using O(n) processors. This algorithm does not require preprocessing the pattern. Therefore, checking for false matches is provably simpler than string matching since string matching takes Ω(log log m) time on the CRCW PRAM. 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.

Original language | English (US) |
---|---|

Pages (from-to) | 512-520 |

Number of pages | 9 |

Journal | Algorithmica (New York) |

Volume | 18 |

Issue number | 4 |

DOIs | |

State | Published - Jan 1 1997 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computer Science(all)
- Computer Science Applications
- Applied Mathematics

### Keywords

- Checking string matching algorithms
- Parallel algorithms
- Randomized (Las Vegas) string matching

### Cite this

*Algorithmica (New York)*,

*18*(4), 512-520. https://doi.org/10.1007/PL00009168

}

*Algorithmica (New York)*, vol. 18, no. 4, pp. 512-520. https://doi.org/10.1007/PL00009168

**Detecting False Matches in String-Matching Algorithms.** / Muthukrishnan, Shan.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Detecting False Matches in String-Matching Algorithms

AU - Muthukrishnan, Shan

PY - 1997/1/1

Y1 - 1997/1/1

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 a false match in O(1) time using O(n) processors. This algorithm does not require preprocessing the pattern. Therefore, checking for false matches is provably simpler than string matching since string matching takes Ω(log log m) time on the CRCW PRAM. 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.

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 a false match in O(1) time using O(n) processors. This algorithm does not require preprocessing the pattern. Therefore, checking for false matches is provably simpler than string matching since string matching takes Ω(log log m) time on the CRCW PRAM. 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.

KW - Checking string matching algorithms

KW - Parallel algorithms

KW - Randomized (Las Vegas) string matching

UR - http://www.scopus.com/inward/record.url?scp=0346339526&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0346339526&partnerID=8YFLogxK

U2 - 10.1007/PL00009168

DO - 10.1007/PL00009168

M3 - Article

AN - SCOPUS:0346339526

VL - 18

SP - 512

EP - 520

JO - Algorithmica

JF - Algorithmica

SN - 0178-4617

IS - 4

ER -