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Finding communities in the form of cohesive subgraphs is a fundamental problem in network analysis. In domains that model networks as undirected graphs, communities are generally associated with dense subgraphs, and many community models have been proposed. Maximal cliques are arguably the most widely studied among such models, with early works dating back to the '60s, and a continuous stream of research up to the present. In domains that model networks as directed graphs, several approaches for community detection have been proposed, but there seems to be no clear model of cohesive subgraph, i.e. , of what a community should look like. We extend the fundamental model of clique to directed graphs, adding the natural constraint of strong connectivity within the clique. We consider in this paper the problem of listing all maximal strongly connected cliques in a directed graph. We first investigate the combinatorial properties of strongly connected cliques and use them to prove that every n -vertex directed graph has at most 3 n / 3 maximal strongly connected cliques. We then exploit these properties to produce the first algorithms with polynomial delay for enumerating maximal strongly connected cliques: a first algorithm with polynomial delay and exponential space usage, and a second one, based on reverse-search, with higher (still polynomial) delay but which uses linear space. 1 1 An extended abstract based on the exponential space algorithm appeared in Conte et al. (2017) [14]. [ABSTRACT FROM AUTHOR]

In this paper, we design a framework to obtain efficient algorithms for several problems with a global constraint (acyclicity or connectivity) such as Connected Dominating Set, Node Weighted Steiner Tree, Maximum Induced Tree, Longest Induced Path, and Feedback Vertex Set. We design a meta-algorithm that solves all these problems and whose running time is upper bounded by $2^{O(k)}\cdot n^{O(1)}$, $2^{O(k \log(k))}\cdot n^{O(1)}$, $2^{O(k^2)}\cdot n^{O(1)}$, and $n^{O(k)}$ where $k$ is respectively the clique-width, $\mathbb{Q}$-rank-width, rank-width, and maximum induced matching width of a given decomposition. Our approach simplifies and unifies the known algorithms for each of the parameters and its running time matches asymptotically also the running times of the best known algorithms for basic \sf NP-hard problems such as Vertex Cover and Dominating Set. Our framework is based on the $d$-neighbor equivalence defined in [B. Bui-Xuan, J. A. Telle, and M. Vatshelle, Theoret. Comput. Sci., (2013), pp. 66--76] and the rank-based approach introduced in [H. L. Bodlaender, M. Cygan, S. Kratsch, and J. Nederlof, Inform. and Comput., 243 (2015), pp. 86--111]. The results we obtain highlight the importance of the $d$-neighbor equivalence relation on the algorithmic applications of width measures. We also prove that our framework could be useful for ${\sf W}[1]$-hard problems parameterized by clique-width such as Max Cut and Maximum Minimal Cut. For these latter problems, we obtain $n^{O(k)}$, $n^{O(k)}$, and $n^{2^{O(k)}}$ time algorithms where $k$ is respectively the clique-width, the $\mathbb{Q}$-rank-width, and the rank-width of the input graph. [ABSTRACT FROM AUTHOR]

In this paper, we prove that, given a clique-width k-expression of an n-vertex graph, Hamiltonian Cycle can be solved in time n O (k) . This improves the naive algorithm that runs in time n O (k 2) by Espelage et al. (Graph-theoretic concepts in computer science, vol 2204. Springer, Berlin, 2001), and it also matches with the lower bound result by Fomin et al. that, unless the Exponential Time Hypothesis fails, there is no algorithm running in time n o (k) (Fomin et al. in SIAM J Comput 43:1541–1563, 2014). We present a technique of representative sets using two-edge colored multigraphs on k vertices. The essential idea is that, for a two-edge colored multigraph, the existence of an Eulerian trail that uses edges with different colors alternately can be determined by two information: the number of colored edges incident with each vertex, and the connectedness of the multigraph. With this idea, we avoid the bottleneck of the naive algorithm, which stores all the possible multigraphs on k vertices with at most n edges. [ABSTRACT FROM AUTHOR]

In the companion paper (Adler et al., 2017), we presented a characterization of the linear rank-width of distance-hereditary graphs, from which we derived an algorithm to compute it in polynomial time. In this paper, we investigate structural properties of distance-hereditary graphs based on this characterization. First, we prove that for a fixed tree T , every distance-hereditary graph of sufficiently large linear rank-width contains a vertex-minor isomorphic to T . We extend this property to bigger graph classes, namely, classes of graphs whose prime induced subgraphs have bounded linear rank-width. Here, prime graphs are graphs containing no splits. We conjecture that for every tree T , every graph of sufficiently large linear rank-width contains a vertex-minor isomorphic to T . Our result implies that it is sufficient to prove this conjecture for prime graphs. For a class Φ of graphs closed under taking vertex-minors, a graph G is called a vertex-minor obstruction for Φ if G ∉ Φ but all of its proper vertex-minors are contained in Φ . Secondly, we provide, for each k ⩾ 2 , a set of distance-hereditary graphs that contains all distance-hereditary vertex-minor obstructions for graphs of linear rank-width at most k . Also, we give a simpler way to obtain the known vertex-minor obstructions for graphs of linear rank-width at most 1. [ABSTRACT FROM AUTHOR]

Abstract: Graph complexity measures such as tree-width, clique-width and rank-width are important because they yield Fixed Parameter Tractable algorithms. These algorithms are based on hierarchical decompositions of the considered graphs, and on boundedness conditions on the graph operations that, more or less explicitly, recombine the components of decompositions into larger graphs. Rank-width is defined in a combinatorial way, based on a tree, and not in terms of graph operations. We define operations on graphs that characterize rank-width and help for the construction of Fixed Parameter Tractable algorithms, especially for problems specified in monadic second-order logic. [Copyright &y& Elsevier]

Abstract: We define a vertex labelling for every planar 3-connected graph with n vertices from which one can answer connectivity queries. A connectivity query asks whether there exists in the given graph a path linking u and v that avoids a set F of edges and a set X of vertices. The vertices u,v and those of X are given by their labels. The edges of F are given by the labels of their ends. Each label has a size of bits. Our construction makes an essential use of straight-line embeddings on grids of simple loop-free planar graphs. Such embeddings can be constructed in linear time by Schnyder''s algorithm [W. Schnyder. Embedding Planar Graphs in the Grid. SODA, First ACM-SIAM Symposium on Discrete Algorithms, San Francisco, pages 138–148, 1990] (see also [H. de Fraysseix, J. Pach, and R. Pollack. Small Sets Supporting Fary Embeddings of Planar Graphs. In Twentieth Annual ACM Symposium on Theory of Computing, pages 426–433. ACM, 1988; H. de Fraysseix, J. Pach, and R. Pollack. How to Draw a Planar Graph on a Grid. Combinatorica, 10:41–51, 1990]). [Copyright &y& Elsevier]