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Dynamic Suffix Array with Polylogarithmic Queries and Updates ...
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Breaking the $O(n)$-Barrier in the Construction of Compressed Suffix Arrays ...
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Time-Space Tradeoffs for Finding a Long Common Substring ...
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Time-Space Tradeoffs for Finding a Long Common Substring ...
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Practical Performance of Space Efficient Data Structures for Longest Common Extensions ...
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Longest Unbordered Factor in Quasilinear Time
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Kociumaka, Tomasz; Kundu, Ritu; Mohamed, Manal. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2018. : LIPIcs - Leibniz International Proceedings in Informatics. 29th International Symposium on Algorithms and Computation (ISAAC 2018), 2018
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Efficient Index for Weighted Sequences
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Barton, Carl; Kociumaka, Tomasz; Pissis, Solon P.. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2016. : LIPIcs - Leibniz International Proceedings in Informatics. 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016), 2016
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Minimal Suffix and Rotation of a Substring in Optimal Time
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Kociumaka, Tomasz. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2016. : LIPIcs - Leibniz International Proceedings in Informatics. 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016), 2016
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Minimal Suffix and Rotation of a Substring in Optimal Time ...
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Kociumaka, Tomasz. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany, 2016
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Sparse Suffix Tree Construction in Optimal Time and Space ...
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Minimal Suffix and Rotation of a Substring in Optimal Time ...
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Optimal Dynamic Strings ...
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Abstract:
In this paper we study the fundamental problem of maintaining a dynamic collection of strings under the following operations: concat - concatenates two strings, split - splits a string into two at a given position, compare - finds the lexicographical order (less, equal, greater) between two strings, LCP - calculates the longest common prefix of two strings. We present an efficient data structure for this problem, where an update requires only $O(\log n)$ worst-case time with high probability, with $n$ being the total length of all strings in the collection, and a query takes constant worst-case time. On the lower bound side, we prove that even if the only possible query is checking equality of two strings, either updates or queries take amortized $Ω(\log n)$ time; hence our implementation is optimal. Such operations can be used as a basic building block to solve other string problems. We provide two examples. First, we can augment our data structure to provide pattern matching queries that may locate ...
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Keyword:
68P05, 68W32; Data Structures and Algorithms cs.DS; F.2.2; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1511.02612 https://arxiv.org/abs/1511.02612
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