295 research outputs found

    Finding Dominators via Disjoint Set Union

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    The problem of finding dominators in a directed graph has many important applications, notably in global optimization of computer code. Although linear and near-linear-time algorithms exist, they use sophisticated data structures. We develop an algorithm for finding dominators that uses only a "static tree" disjoint set data structure in addition to simple lists and maps. The algorithm runs in near-linear or linear time, depending on the implementation of the disjoint set data structure. We give several versions of the algorithm, including one that computes loop nesting information (needed in many kinds of global code optimization) and that can be made self-certifying, so that the correctness of the computed dominators is very easy to verify

    Monotone Grid Drawings of Planar Graphs

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    A monotone drawing of a planar graph GG is a planar straight-line drawing of GG where a monotone path exists between every pair of vertices of GG in some direction. Recently monotone drawings of planar graphs have been proposed as a new standard for visualizing graphs. A monotone drawing of a planar graph is a monotone grid drawing if every vertex in the drawing is drawn on a grid point. In this paper we study monotone grid drawings of planar graphs in a variable embedding setting. We show that every connected planar graph of nn vertices has a monotone grid drawing on a grid of size O(n)×O(n2)O(n)\times O(n^2), and such a drawing can be found in O(n) time

    Unions of Onions: Preprocessing Imprecise Points for Fast Onion Decomposition

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    Let D\mathcal{D} be a set of nn pairwise disjoint unit disks in the plane. We describe how to build a data structure for D\mathcal{D} so that for any point set PP containing exactly one point from each disk, we can quickly find the onion decomposition (convex layers) of PP. Our data structure can be built in O(nlogn)O(n \log n) time and has linear size. Given PP, we can find its onion decomposition in O(nlogk)O(n \log k) time, where kk is the number of layers. We also provide a matching lower bound. Our solution is based on a recursive space decomposition, combined with a fast algorithm to compute the union of two disjoint onionComment: 10 pages, 5 figures; a preliminary version appeared at WADS 201

    A second look at the toric h-polynomial of a cubical complex

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    We provide an explicit formula for the toric hh-contribution of each cubical shelling component, and a new combinatorial model to prove Clara Chan's result on the non-negativity of these contributions. Our model allows for a variant of the Gessel-Shapiro result on the gg-polynomial of the cubical lattice, this variant may be shown by simple inclusion-exclusion. We establish an isomorphism between our model and Chan's model and provide a reinterpretation in terms of noncrossing partitions. By discovering another variant of the Gessel-Shapiro result in the work of Denise and Simion, we find evidence that the toric hh-polynomials of cubes are related to the Morgan-Voyce polynomials via Viennot's combinatorial theory of orthogonal polynomials.Comment: Minor correction

    Another look at graph coloring via propositional satisfiability

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    AbstractThis paper studies the solution of graph coloring problems by encoding into propositional satisfiability problems. The study covers three kinds of satisfiability solvers, based on postorder reasoning (e.g., grasp, chaff), preorder reasoning (e.g., 2cl, 2clsEq), and back-chaining (modoc). The study evaluates three encodings, one of them believed to be new. Some new symmetry-breaking methods, specific to coloring, are used to reduce the redundancy of solutions. A by-product of this research is an implemented lower-bound technique that has shown improved lower bounds for the chromatic numbers of the long-standing unsolved random graphs known as DSJC125.5 and DSJC125.9. Independent-set analysis shows that the chromatic numbers of DSJC125.5 and DSJC125.9 are at least 18 and 40, respectively, but satisfiability encoding was able to demonstrate only that the chromatic numbers are at least 13 and 38, respectively, within available time and space
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