11,801 research outputs found

    Split decomposition and graph-labelled trees: characterizations and fully-dynamic algorithms for totally decomposable graphs

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    In this paper, we revisit the split decomposition of graphs and give new combinatorial and algorithmic results for the class of totally decomposable graphs, also known as the distance hereditary graphs, and for two non-trivial subclasses, namely the cographs and the 3-leaf power graphs. Precisely, we give strutural and incremental characterizations, leading to optimal fully-dynamic recognition algorithms for vertex and edge modifications, for each of these classes. These results rely on a new framework to represent the split decomposition, namely the graph-labelled trees, which also captures the modular decomposition of graphs and thereby unify these two decompositions techniques. The point of the paper is to use bijections between these graph classes and trees whose nodes are labelled by cliques and stars. Doing so, we are also able to derive an intersection model for distance hereditary graphs, which answers an open problem.Comment: extended abstract appeared in ISAAC 2007: Dynamic distance hereditary graphs using split decompositon. In International Symposium on Algorithms and Computation - ISAAC. Number 4835 in Lecture Notes, pages 41-51, 200

    Limits of Ordered Graphs and their Applications

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    The emerging theory of graph limits exhibits an analytic perspective on graphs, showing that many important concepts and tools in graph theory and its applications can be described more naturally (and sometimes proved more easily) in analytic language. We extend the theory of graph limits to the ordered setting, presenting a limit object for dense vertex-ordered graphs, which we call an \emph{orderon}. As a special case, this yields limit objects for matrices whose rows and columns are ordered, and for dynamic graphs that expand (via vertex insertions) over time. Along the way, we devise an ordered locality-preserving variant of the cut distance between ordered graphs, showing that two graphs are close with respect to this distance if and only if they are similar in terms of their ordered subgraph frequencies. We show that the space of orderons is compact with respect to this distance notion, which is key to a successful analysis of combinatorial objects through their limits. We derive several applications of the ordered limit theory in extremal combinatorics, sampling, and property testing in ordered graphs. In particular, we prove a new ordered analogue of the well-known result by Alon and Stav [RS\&A'08] on the furthest graph from a hereditary property; this is the first known result of this type in the ordered setting. Unlike the unordered regime, here the random graph model G(n,p)G(n, p) with an ordering over the vertices is \emph{not} always asymptotically the furthest from the property for some pp. However, using our ordered limit theory, we show that random graphs generated by a stochastic block model, where the blocks are consecutive in the vertex ordering, are (approximately) the furthest. Additionally, we describe an alternative analytic proof of the ordered graph removal lemma [Alon et al., FOCS'17].Comment: Added a new application: An Alon-Stav type result on the furthest ordered graph from a hereditary property; Fixed and extended proof sketch of the removal lemma applicatio

    The b-Matching Problem in Distance-Hereditary Graphs and Beyond

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    We make progress on the fine-grained complexity of Maximum-Cardinality Matching on graphs of bounded clique-width. Quasi linear-time algorithms for this problem have been recently proposed for the important subclasses of bounded-treewidth graphs (Fomin et al., SODA\u2717) and graphs of bounded modular-width (Coudert et al., SODA\u2718). We present such algorithm for bounded split-width graphs - a broad generalization of graphs of bounded modular-width, of which an interesting subclass are the distance-hereditary graphs. Specifically, we solve Maximum-Cardinality Matching in O((k log^2{k})*(m+n) * log{n})-time on graphs with split-width at most k. We stress that the existence of such algorithm was not even known for distance-hereditary graphs until our work. Doing so, we improve the state of the art (Dragan, WG\u2797) and we answer an open question of (Coudert et al., SODA\u2718). Our work brings more insights on the relationships between matchings and splits, a.k.a., join operations between two vertex-subsets in different connected components. Furthermore, our analysis can be extended to the more general (unit cost) b-Matching problem. On the way, we introduce new tools for b-Matching and dynamic programming over split decompositions, that can be of independent interest

    A Single-Exponential Fixed-Parameter Algorithm for Distance-Hereditary Vertex Deletion

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    Vertex deletion problems ask whether it is possible to delete at most kk vertices from a graph so that the resulting graph belongs to a specified graph class. Over the past years, the parameterized complexity of vertex deletion to a plethora of graph classes has been systematically researched. Here we present the first single-exponential fixed-parameter tractable algorithm for vertex deletion to distance-hereditary graphs, a well-studied graph class which is particularly important in the context of vertex deletion due to its connection to the graph parameter rank-width. We complement our result with matching asymptotic lower bounds based on the exponential time hypothesis. As an application of our algorithm, we show that a vertex deletion set to distance-hereditary graphs can be used as a parameter which allows single-exponential fixed-parameter tractable algorithms for classical NP-hard problems.Comment: 43 pages, 9 figures (revised journal version; an extended abstract appeared in the proceedings of MFCS 2016

    Hamilton cycles in almost distance-hereditary graphs

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    Let GG be a graph on n≥3n\geq 3 vertices. A graph GG is almost distance-hereditary if each connected induced subgraph HH of GG has the property dH(x,y)≤dG(x,y)+1d_{H}(x,y)\leq d_{G}(x,y)+1 for any pair of vertices x,y∈V(H)x,y\in V(H). A graph GG is called 1-heavy (2-heavy) if at least one (two) of the end vertices of each induced subgraph of GG isomorphic to K1,3K_{1,3} (a claw) has (have) degree at least n/2n/2, and called claw-heavy if each claw of GG has a pair of end vertices with degree sum at least nn. Thus every 2-heavy graph is claw-heavy. In this paper we prove the following two results: (1) Every 2-connected, claw-heavy and almost distance-hereditary graph is Hamiltonian. (2) Every 3-connected, 1-heavy and almost distance-hereditary graph is Hamiltonian. In particular, the first result improves a previous theorem of Feng and Guo. Both results are sharp in some sense.Comment: 14 pages; 1 figure; a new theorem is adde
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