64,172 research outputs found

    PACE Solver Description: Bute-Plus: A Bottom-Up Exact Solver for Treedepth

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    This note introduces Bute-Plus, an exact solver for the treedepth problem. The core of the solver is a positive-instance driven dynamic program that constructs an elimination tree of minimum depth in a bottom-up fashion. Three features greatly improve the algorithm's run time. The first of these is a specialised trie data structure. The second is a domination rule. The third is a heuristic presolve step can quickly find a treedepth decomposition of optimal depth for many instances.Comment: 4 pages, 1 appendix pages, 0 figures. A version of this tool description paper without the appendix is published in the proceedings of IPEC 2020: https://drops.dagstuhl.de/opus/volltexte/2020/13337/pdf/LIPIcs-IPEC-2020-34.pdf . Changes: this version expands the paper from a preliminary versio

    Incremental 22-Edge-Connectivity in Directed Graphs

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    In this paper, we initiate the study of the dynamic maintenance of 22-edge-connectivity relationships in directed graphs. We present an algorithm that can update the 22-edge-connected blocks of a directed graph with nn vertices through a sequence of mm edge insertions in a total of O(mn)O(mn) time. After each insertion, we can answer the following queries in asymptotically optimal time: (i) Test in constant time if two query vertices vv and ww are 22-edge-connected. Moreover, if vv and ww are not 22-edge-connected, we can produce in constant time a "witness" of this property, by exhibiting an edge that is contained in all paths from vv to ww or in all paths from ww to vv. (ii) Report in O(n)O(n) time all the 22-edge-connected blocks of GG. To the best of our knowledge, this is the first dynamic algorithm for 22-connectivity problems on directed graphs, and it matches the best known bounds for simpler problems, such as incremental transitive closure.Comment: Full version of paper presented at ICALP 201

    Finger Search in Grammar-Compressed Strings

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    Grammar-based compression, where one replaces a long string by a small context-free grammar that generates the string, is a simple and powerful paradigm that captures many popular compression schemes. Given a grammar, the random access problem is to compactly represent the grammar while supporting random access, that is, given a position in the original uncompressed string report the character at that position. In this paper we study the random access problem with the finger search property, that is, the time for a random access query should depend on the distance between a specified index ff, called the \emph{finger}, and the query index ii. We consider both a static variant, where we first place a finger and subsequently access indices near the finger efficiently, and a dynamic variant where also moving the finger such that the time depends on the distance moved is supported. Let nn be the size the grammar, and let NN be the size of the string. For the static variant we give a linear space representation that supports placing the finger in O(logN)O(\log N) time and subsequently accessing in O(logD)O(\log D) time, where DD is the distance between the finger and the accessed index. For the dynamic variant we give a linear space representation that supports placing the finger in O(logN)O(\log N) time and accessing and moving the finger in O(logD+loglogN)O(\log D + \log \log N) time. Compared to the best linear space solution to random access, we improve a O(logN)O(\log N) query bound to O(logD)O(\log D) for the static variant and to O(logD+loglogN)O(\log D + \log \log N) for the dynamic variant, while maintaining linear space. As an application of our results we obtain an improved solution to the longest common extension problem in grammar compressed strings. To obtain our results, we introduce several new techniques of independent interest, including a novel van Emde Boas style decomposition of grammars

    Cross-Document Pattern Matching

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    We study a new variant of the string matching problem called cross-document string matching, which is the problem of indexing a collection of documents to support an efficient search for a pattern in a selected document, where the pattern itself is a substring of another document. Several variants of this problem are considered, and efficient linear-space solutions are proposed with query time bounds that either do not depend at all on the pattern size or depend on it in a very limited way (doubly logarithmic). As a side result, we propose an improved solution to the weighted level ancestor problem

    Weighted ancestors in suffix trees

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    The classical, ubiquitous, predecessor problem is to construct a data structure for a set of integers that supports fast predecessor queries. Its generalization to weighted trees, a.k.a. the weighted ancestor problem, has been extensively explored and successfully reduced to the predecessor problem. It is known that any solution for both problems with an input set from a polynomially bounded universe that preprocesses a weighted tree in O(n polylog(n)) space requires \Omega(loglogn) query time. Perhaps the most important and frequent application of the weighted ancestors problem is for suffix trees. It has been a long-standing open question whether the weighted ancestors problem has better bounds for suffix trees. We answer this question positively: we show that a suffix tree built for a text w[1..n] can be preprocessed using O(n) extra space, so that queries can be answered in O(1) time. Thus we improve the running times of several applications. Our improvement is based on a number of data structure tools and a periodicity-based insight into the combinatorial structure of a suffix tree.Comment: 27 pages, LNCS format. A condensed version will appear in ESA 201
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