Constant-Time Randomized Parallel String Matching
Given a pattern string of length m for the string-matching problem, we design an algorithm that computes deterministic samples of a sufficiently long substring of the pattern in constant time. This problem used to be the bottleneck in the pattern preprocessing for one- and two-dimensional pattern ma...
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| Vydané v: | SIAM journal on computing Ročník 26; číslo 4; s. 950 - 960 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Philadelphia, PA
Society for Industrial and Applied Mathematics
01.08.1997
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| Predmet: | |
| ISSN: | 0097-5397, 1095-7111 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Given a pattern string of length m for the string-matching problem, we design an algorithm that computes deterministic samples of a sufficiently long substring of the pattern in constant time. This problem used to be the bottleneck in the pattern preprocessing for one- and two-dimensional pattern matching. The best previous time bound was O(log2m / log log m). We use this algorithm to obtain the following results (all algorithms below are optimal parallel algorithms on a CRCW PRAM): a deterministic string-matching algorithm which takes O(log log m) time for preprocessing and constant time for text search, which are the best possible in both preprocessing and text search; a constant-time deterministic string-matching algorithm in the case where the text length n satisfies $n=\Omega(m^{1+\epsilon})$ for a constant $\epsilon > 0$; a simple string-matching algorithm that has constant time with high probability for random input; the main result: a constant-expected-time Las Vegas algorithm for computing the period of the pattern and all witnesses and thus for string matching itself; in both cases, an $\Omega(\log\log m)$ lower bound is known for deterministic algorithms. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 content type line 14 |
| ISSN: | 0097-5397 1095-7111 |
| DOI: | 10.1137/S009753979528007X |