{"title":"About the Authors","authors":"Larry Dooley, R. D. Blackburn","doi":"10.1177/1529100614554912","DOIUrl":null,"url":null,"abstract":"Crochemore repetition algorithm introduced in 1981 was the first O(n log n) algorithm for computing repetitions. Since then, several linear-time worst-case algorithms for computing runs have been introduced. They all follow a similar strategy – first compute the suffix tree or array, then use the suffix tree or array to compute the Lempel-Ziv factorization, then using the Lempel-Ziv factorization compute all the runs. It is conceivable that in practice an extension of Crochemore repetition algorithm may outperform the linear-time algorithms, or at least for certain classes of strings. The nature of Crochemore algorithm lends itself naturally to parallelization, while the linear-time algorithms are not easily conducive to parallelization. For all these reasons it is interesting to explore ways to extend the original Crochemore repetition algorithm to compute runs. We present three variants of extending the repetition algorithm to compute runs – two with a worsen complexity of O(n log n), and one with the same complexity as the original algorithm. The three variants are tested for speed of performance and their memory requirements are analyzed.","PeriodicalId":20879,"journal":{"name":"Psychological Science in the Public Interest","volume":"15 1","pages":"ii - iii"},"PeriodicalIF":18.2000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1529100614554912","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological Science in the Public Interest","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/1529100614554912","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Crochemore repetition algorithm introduced in 1981 was the first O(n log n) algorithm for computing repetitions. Since then, several linear-time worst-case algorithms for computing runs have been introduced. They all follow a similar strategy – first compute the suffix tree or array, then use the suffix tree or array to compute the Lempel-Ziv factorization, then using the Lempel-Ziv factorization compute all the runs. It is conceivable that in practice an extension of Crochemore repetition algorithm may outperform the linear-time algorithms, or at least for certain classes of strings. The nature of Crochemore algorithm lends itself naturally to parallelization, while the linear-time algorithms are not easily conducive to parallelization. For all these reasons it is interesting to explore ways to extend the original Crochemore repetition algorithm to compute runs. We present three variants of extending the repetition algorithm to compute runs – two with a worsen complexity of O(n log n), and one with the same complexity as the original algorithm. The three variants are tested for speed of performance and their memory requirements are analyzed.
期刊介绍:
Psychological Science in the Public Interest (PSPI) is a distinctive journal that provides in-depth and compelling reviews on issues directly relevant to the general public. Authored by expert teams with diverse perspectives, these reviews aim to evaluate the current state-of-the-science on various topics. PSPI reports have addressed issues such as questioning the validity of the Rorschach and other projective tests, examining strategies to maintain cognitive sharpness in aging brains, and highlighting concerns within the field of clinical psychology. Notably, PSPI reports are frequently featured in Scientific American Mind and covered by various major media outlets.