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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/11286
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dc.contributor.advisorFranek, Frantiseken_US
dc.contributor.advisorAntoine Deza, Emil Sekerinskien_US
dc.contributor.advisorAntoine Deza, Emil Sekerinskien_US
dc.contributor.authorWeng, Chia-Chunen_US
dc.date.accessioned2014-06-18T16:54:09Z-
dc.date.available2014-06-18T16:54:09Z-
dc.date.created2011-09-23en_US
dc.date.issued2011-10en_US
dc.identifier.otheropendissertations/6266en_US
dc.identifier.other7252en_US
dc.identifier.other2253075en_US
dc.identifier.urihttp://hdl.handle.net/11375/11286-
dc.description.abstract<p>In the first part of this thesis we present a C++ implementation of an improved O(n log n) algorithm to compute runs, number of primitively rooted distinct squares, and maximal repetitions, based on Crochemore's partitioning algorithm. This is a joint work with Mei Jiang and extends her work on the problem. In the second part we present a C++ implementation of a linear algorithm to compute runs based on the Main's, and Kolpakov and Kucherov's algorithms following the strategy:</p> <p>1. Compute suffix array and LCP array in linear time;</p> <p>2. Using the suffix array and LCP array, compute Lempel-Ziv factorization in linear time;</p> <p>3. Using the Lempel-Ziv factorization, compute in linear time some of the runs that include all the leftmost runs following Main's algorithm;</p> <p>4. Using Kolpakov and Kucherov's approach, compute in linear time the rest of all the runs.</p> <p>For our linear time implementation, we partially relied on Jonathan Fischer's Java implementation.</p>en_US
dc.subjectrunen_US
dc.subjectrepetitionen_US
dc.subjectperiodicityen_US
dc.subjectstringen_US
dc.subjectTheory and Algorithmsen_US
dc.subjectTheory and Algorithmsen_US
dc.titleImplementing Efficient Algorithms for Computing Runsen_US
dc.typethesisen_US
dc.contributor.departmentComputing and Softwareen_US
dc.description.degreeMaster of Science (MSc)en_US
Appears in Collections:Open Access Dissertations and Theses

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