Single-edge monotonic sequences of graphs and linear-time algorithms for minimal completions and deletions

AbstractWe study graph properties that admit an increasing, or equivalently decreasing, sequence of graphs on the same vertex set such that for any two consecutive graphs in the sequence their difference is a single edge. This is useful for characterizing and computing minimal completions and deletions of arbitrary graphs into having these properties. We prove that threshold graphs and chain graphs admit such sequences. Based on this characterization and other structural properties, we present linear-time algorithms both for computing minimal completions and deletions into threshold, chain, and bipartite graphs, and for extracting a minimal completion or deletion from a given completion or deletion. Minimum completions and deletions into these classes are NP-hard to compute

Efficient enumeration of maximal split subgraphs and sub-cographs and related classes

In this paper, we are interested in algorithms that take in input an arbitrary graph $G$, and that enumerate in output all the (inclusion-wise) maximal "subgraphs" of $G$ which fulfil a given property $\Pi$. All over this paper, we study several different properties $\Pi$, and the notion of subgraph under consideration (induced or not) will vary from a result to another. More precisely, we present efficient algorithms to list all maximal split subgraphs, sub-cographs and some subclasses of cographs of a given input graph. All the algorithms presented here run in polynomial delay, and moreover for split graphs it only requires polynomial space. In order to develop an algorithm for maximal split (edge-)subgraphs, we establish a bijection between the maximal split subgraphs and the maximal independent sets of an auxiliary graph. For cographs and some subclasses , the algorithms rely on a framework recently introduced by Conte & Uno called Proximity Search. Finally we consider the extension problem, which consists in deciding if there exists a maximal induced subgraph satisfying a property $\Pi$ that contains a set of prescribed vertices and that avoids another set of vertices. We show that this problem is NP-complete for every "interesting" hereditary property $\Pi$. We extend the hardness result to some specific edge version of the extension problem

Fast minimal triangulation algorithm using minimum degree criterion

AbstractWe propose an algorithm for minimal triangulation which, using simple and efficient strategy, subdivides the input graph in different, almost non-overlapping, subgraphs. Using the technique of matrix multiplication for saturating the minimal separators, we show that the partition of the graph can be computed in time O(nα) where nα is the time required by the binary matrix multiplication. After saturating the minimal separators, the same procedure is recursively applied on each subgraphs. We also present a variant of the algorithm in which the minimum degree criterion is used. In this way, we obtain an algorithm that uses minimum degree criterion and at the same time produces a minimal triangulation, thus shedding new light on the effectiveness of the minimum degree heuristics

SCENELAB: Scene Labelling by a Society of Agents; A Distributed Constraint Propagation System

This paper describes SCENELAB, a computer system for labelling line drawings of scenes in simple polyhedral worlds. The key idea behind SCENELAB is to bring together the concept of contraint-based filtering algorithms and the paradigm of societies of cooperating agents. The problem of finding labellings for pictures drawn from blocks world scenes has been taken as a sample application. Clearly, this makes SCENELAB no vision system, but we claim that a system designed along these lines could be part of a real vision system. Following e.g. Alan Mackworth, we argue that constraint exploitation on resp. between various representational levels is a key technique of ‘seeing things'. Furthermore, constraints and constraint propagation neatly fit into the framework of societies of agents, realized by asynchronuously concurrent processing units and message passing mechanisms. SCENELAB, as it is actually running, can be used to specify and solve arbitrary Labelling problems that can be seen as instances of a particular class of simple constraint problems based on finite, pseudo-transitive binary constraints. However, it is felt that the overall approach generalizes to arbitrary constraint problems. Emphasis is given to a mathematical model of the problem and its solution, to be able to specify the reasoning techniques of SCENELAB, and to identify the class of problems it can handle. I tried to shed some Light onto the methodological background of SCENELAB, which seems necessary to judge the achievements and disachievements of the present work. After some introductory chapters on the key concepts involved in SCENELAB, (scene) labelling problems, constraint propagation, and societies of agents, an overview on both the structure and behavior of SCENELAB is given in part B of the paper. In part C, then, an algebraic model is introduced, which serves as a base for discussing several approaches to labelling problems, namely Waltz's original Landmark algorithm, a synchronized parallel solution suggested by Azriel Rosenfeld, and clearly, the present approach. A proof of the correctness of SCENELABs algorithms is included. This proof takes into account the specifities of systems of asynchronously communicating agents where no global state is observable

Gene Family Histories: Theory and Algorithms

Detailed gene family histories and reconciliations with species trees are a prerequisite for studying associations between genetic and phenotypic innovations. Even though the true evolutionary scenarios are usually unknown, they impose certain constraints on the mathematical structure of data obtained from simple yes/no questions in pairwise comparisons of gene sequences. Recent advances in this field have led to the development of methods for reconstructing (aspects of) the scenarios on the basis of such relation data, which can most naturally be represented by graphs on the set of considered genes. We provide here novel characterizations of best match graphs (BMGs) which capture the notion of (reciprocal) best hits based on sequence similarities. BMGs provide the basis for the detection of orthologous genes (genes that diverged after a speciation event). There are two main sources of error in pipelines for orthology inference based on BMGs. Firstly, measurement errors in the estimation of best matches from sequence similarity in general lead to violations of the characteristic properties of BMGs. The second issue concerns the reconstruction of the orthology relation from a BMG. We show how to correct estimated BMG to mathematically valid ones and how much information about orthologs is contained in BMGs. We then discuss implicit methods for horizontal gene transfer (HGT) inference that focus on pairs of genes that have diverged only after the divergence of the two species in which the genes reside. This situation defines the edge set of an undirected graph, the later-divergence-time (LDT) graph. We explore the mathematical structure of LDT graphs and show how much information about all HGT events is contained in such LDT graphs

Proceedings of the 26th International Symposium on Theoretical Aspects of Computer Science (STACS'09)

The Symposium on Theoretical Aspects of Computer Science (STACS) is held alternately in France and in Germany. The conference of February 26-28, 2009, held in Freiburg, is the 26th in this series. Previous meetings took place in Paris (1984), Saarbr¨ucken (1985), Orsay (1986), Passau (1987), Bordeaux (1988), Paderborn (1989), Rouen (1990), Hamburg (1991), Cachan (1992), W¨urzburg (1993), Caen (1994), M¨unchen (1995), Grenoble (1996), L¨ubeck (1997), Paris (1998), Trier (1999), Lille (2000), Dresden (2001), Antibes (2002), Berlin (2003), Montpellier (2004), Stuttgart (2005), Marseille (2006), Aachen (2007), and Bordeaux (2008). ..

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum