Verifying Monadic Second-Order Properties of Graph Programs

Poskitt, Christopher M.; Plump, Detlef

doi:10.1007/978-3-319-09108-2_3

Cited by 26 publications

(37 citation statements)

References 15 publications

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“…different application scenarios from the graph database domain [37] as presented in this paper, but also to other domains such as model-driven engineering, where our approach can be used, e.g., to generate test models for model transformations [2,11,22]. We also aim at generalizing our approach to more expressive graph properties able to encode, e.g., path-related properties [28,27,21]. Finally, the work on exploration and compaction of extracted symbolic models as well as reducing their number during tableau construction is an ongoing task.…”

Section: Discussionmentioning

confidence: 99%

Symbolic Model Generation for Graph Properties

Schneider

Lambers

Orejas

2017

Fundamental Approaches to Software Engineering

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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.

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Section: Discussionmentioning

confidence: 99%

Symbolic Model Generation for Graph Properties

Schneider

Lambers

Orejas

2017

Fundamental Approaches to Software Engineering

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“…Guards may be used to restrict the application of the program rules. A recent extension to Plump's work [35] introduces a Hoare logic for verifying graph programs. Although formulated in a different setting, the problem has several points of contact with our own effort to verify properties of coordination patterns.…”

Section: Related Workmentioning

confidence: 98%

Reasoning about software reconfigurations: The behavioural and structural perspectives

Oliveira

Barbosa

2015

Science of Computer Programming

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Software connectors encapsulate interaction patterns between services in complex, distributed service-oriented applications. Such patterns encode the interconnection between the architectural elements in a system, which is not necessarily fixed, but often evolves dynamically. This may happen in response to faults, degrading levels of QoS, new enforced requirements or the re-assessment of contextual conditions. To be able to characterise and reason about such changes became a major issue in the project of trustworthy software. This paper discusses what reconfiguration means within coordination-based models of software design. In these models computation and interaction are kept separate: components and services interact anonymously through specific connectors encoding the coordination protocols. In such a setting, of which Reo is a paradigmatic illustration, the paper introduces a model for connector reconfigurations, from both a structural and a behavioural perspective.

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“…A main problem of (first-order) graph logics is that it is not possible to express relevant properties like "there is a path from node n to n ", because they are not first-order. As a consequence, there have been a number of proposals that try to overcome this limitation by extending existing logics, like [7,12,8]. In particular, in [8] we extended the LNGC, allowing us to state properties about paths in graphs and to reason about them in a generic way (i.e.…”

Section: Introductionmentioning

confidence: 99%