A logic of graph conditions extended with paths

In this paper we tackle the problem of extending the logic of nested graph conditions with paths. This means, for instance, that we may state properties about the existence of paths between some given nodes. As a main contribution, a sound and complete tableau method is defined for reasoning about this kind of properties.Peer ReviewedPostprint (published version

Towards a navigational logic for graphical structures

One of the main advantages of the Logic of Nested Conditions, defined by Habel and Pennemann, for reasoning about graphs, is its generality: this logic can be used in the framework of many classes of graphs and graphical structures. It is enough that the category of these structures satisfies certain basic conditions. In a previous paper [14], we extended this logic to be able to deal with graph properties including paths, but this extension was only defined for the category of untyped directed graphs. In addition it seemed difficult to talk about paths abstractly, that is, independently of the given category of graphical structures. In this paper we approach this problem. In particular, given an arbitrary category of graphical structures, we assume that for every object of this category there is an associated edge relation that can be used to define a path relation. Moreover, we consider that edges have some kind of labels and paths can be specified by associating them to a set of label sequences. Then, after the presentation of that general framework, we show how it can be applied to several classes of graphs. Moreover, we present a set of sound inference rules for reasoning in the logic.Peer ReviewedPostprint (author's final draft

Verifying Monadic Second-Order Properties of Graph Programs

The core challenge in a Hoare- or Dijkstra-style proof system for graph programs is in defining a weakest liberal precondition construction with respect to a rule and a postcondition. Previous work addressing this has focused on assertion languages for first-order properties, which are unable to express important global properties of graphs such as acyclicity, connectedness, or existence of paths. In this paper, we extend the nested graph conditions of Habel, Pennemann, and Rensink to make them equivalently expressive to monadic second-order logic on graphs. We present a weakest liberal precondition construction for these assertions, and demonstrate its use in verifying non-local correctness specifications of graph programs in the sense of Habel et al.Comment: Extended version of a paper to appear at ICGT 201

Rewriting Abstract Structures: Materialization Explained Categorically

The paper develops an abstract (over-approximating) semantics for double-pushout rewriting of graphs and graph-like objects. The focus is on the so-called materialization of left-hand sides from abstract graphs, a central concept in previous work. The first contribution is an accessible, general explanation of how materializations arise from universal properties and categorical constructions, in particular partial map classifiers, in a topos. Second, we introduce an extension by enriching objects with annotations and give a precise characterization of strongest post-conditions, which are effectively computable under certain assumptions

Symbolic model generation for graph properties

Graphs are ubiquitous in Computer Science. For this reason, in many areas, it is very important to have the means to express and reason about graph properties. In particular, we want to be able to check automatically if a given graph property is satisfiable. Actually, in most application scenarios it is desirable to be able to explore graphs satisfying the graph property if they exist or even to get a complete and compact overview of the graphs satisfying the graph property. We show that the tableau-based reasoning method for graph properties as introduced by Lambers and Orejas paves the way for a symbolic model generation algorithm for graph properties. Graph properties are formulated in a dedicated logic making use of graphs and graph morphisms, which is equivalent to first-order logic on graphs as introduced by Courcelle. Our parallelizable algorithm gradually generates a finite set of so-called symbolic models, where each symbolic model describes a set of finite graphs (i.e., finite models) satisfying the graph property. The set of symbolic models jointly describes all finite models for the graph property (complete) and does not describe any finite graph violating the graph property (sound). Moreover, no symbolic model is already covered by another one (compact). Finally, the algorithm is able to generate from each symbolic model a minimal finite model immediately and allows for an exploration of further finite models. The algorithm is implemented in the new tool AutoGraph.Peer ReviewedPostprint (author's final draft

Proving Correctness of Graph Programs Relative to Recursively Nested Conditions

We propose a new specification language for the proof-based approach to verification of graph programs by introducing mu-conditions as an alternative to existing formalisms which can express path properties. The contributions of this paper are the lifting of constructions from nested conditions to the new, more expressive conditions and a proof calculus for partial correctness relative to mu-conditions. In particular, we exhibit and prove the correctness of a construction to compute weakest preconditions with respect to finite graph programs

Automated reasoning for attributed graph properties

Graphs are ubiquitous in computer science. Moreover, in various application fields, graphs are equipped with attributes to express additional information such as names of entities or weights of relationships. Due to the pervasiveness of attributed graphs, it is highly important to have the means to express properties on attributed graphs to strengthen modeling capabilities and to enable analysis. Firstly, we introduce a new logic of attributed graph properties, where the graph part and attribution part are neatly separated. The graph part is equivalent to first-order logic on graphs as introduced by Courcelle. It employs graph morphisms to allow the specification of complex graph patterns. The attribution part is added to this graph part by reverting to the symbolic approach to graph attribution, where attributes are represented symbolically by variables whose possible values are specified by a set of constraints making use of algebraic specifications. Secondly, we extend our refutationally complete tableau-based reasoning method as well as our symbolic model generation approach for graph properties to attributed graph properties. Due to the new logic mentioned above, neatly separating the graph and attribution parts, and the categorical constructions employed only on a more abstract level, we can leave the graph part of the algorithms seemingly unchanged. For the integration of the attribution part into the algorithms, we use an oracle, allowing for flexible adoption of different available SMT solvers in the actual implementation. Finally, our automated reasoning approach for attributed graph properties is implemented in the tool AutoGraph integrating in particular the SMT solver Z3 for the attribute part of the properties. We motivate and illustrate our work with a particular application scenario on graph database query validation.Peer ReviewedPostprint (author's final draft

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 22nd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2019. The 29 papers presented in this volume were carefully reviewed and selected from 85 submissions. They deal with foundational research with a clear significance for software science

Environnement d'assistance au développement de transformations de graphes correctes

Les travaux de cette thèse ont pour cadre la vérification formelle, et plus spécifiquement le projet ANR Blanc CLIMT (Categorical and Logical Methods in Model Transformation) dédié aux grammaires de graphes. Ce projet, qui a démarré en février 2012 pour une durée de 48 mois, a donné lieu à la définition du langage Small-tALC, bâti sur la logique de description ALCQI. Ce langage prend la forme d’un DSL (Domain Specific Language) impératif à base de règles, chacune dérivant structurellement un graphe. Le langage s’accompagne d’un composant de preuve basé sur la logique de Hoare chargé d’automatiser le processus de vérification d’une règle. Cependant, force est de constater que tous les praticiens ne sont pas nécessairement familiers avec les méthodes formelles du génie logiciel et que les transformations sont complexes à écrire. En particulier, ne disposant que du seul prouveur, il s’agit pour le développeur Small-tALC d’écrire un triplet de Hoare {P} S {Q} et d’attendre le verdict de sa correction sous la forme d’un graphe contre-exemple en cas d’échec. Ce contre-exemple est parfois difficile à décrypter, et ne permet pas de localiser aisément l’erreur au sein du triplet. De plus, le prouveur ne valide qu’une seule règle à la fois, sans considérer l’ensemble des règles de transformation et leur ordonnancement d’exécution. Ce constat nous a conduits à proposer un environnement d’assistance au développeur Small-tALC. Cette assistance vise à l’aider à rédiger ses triplets et à prouver ses transformations, en lui offrant plus de rétroaction que le prouveur. Pour ce faire, les instructions du langage ont été revisitées selon l’angle ABox et TBox de la logique ALCQI. Ainsi, conformément aux logiques de description, la mise à jour du graphe par la règle s’assimile à la mise à jour ABox des individus (les nœuds) et de leurs relations (les arcs) d’un domaine terminologique TBox (le type des nœuds et les étiquettes des arcs) susceptible d’évoluer. Les contributions de cette thèse concernent : (1) un extracteur de préconditions ABox à partir d’un code de transformation S et de sa postcondition Q pour l’écriture d’une règle {P} S {Q} correcte par construction, (2) un raisonneur TBox capable d’inférer des propriétés sur des ensembles de nœuds transformés par un enchaînement de règles {Pi} Si {Qi}, et (3) d’autres diagnostics ABox et TBox sous la forme de tests afin d’identifier et de localiser des problèmes dans les programmes. L’analyse statique du code de transformation d’une règle, combinée à un calcul d’alias des variables désignant les nœuds du graphe, permet d’extraire un ensemble de préconditions ABox validant la règle. Les inférences TBox pour un enchaînement de règles résultent d’une analyse statique par interprétation abstraite des règles ABox afin de vérifier formellement des états du graphe avant et après les appels des règles. A ces deux outils formels s’ajoutent des analyseurs dynamiques produisant une batterie de tests pour une règle ABox, ou un diagnostic TBox pour une séquence de règle