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Graph queries have lately gained increased interest due to application areas such as social networks, biological networks, or model queries. For the relational database case the relational algebra and generalized discrimination networks have been studied to find appropriate decompositions into subqueries and ordering of these subqueries for query evaluation or incremental updates of query results. For graph database queries however there is no formal underpinning yet that allows us to find such suitable operationalizations. Consequently, we suggest a simple operational concept for the decomposition of arbitrary complex queries into simpler subqueries and the ordering of these subqueries in form of generalized discrimination networks for graph queries inspired by the relational case. The approach employs graph transformation rules for the nodes of the network and thus we can employ the underlying theory. We further show that the proposed generalized discrimination networks have the same expressive power as nested graph conditions.
Complex projects developed under the model-driven engineering paradigm nowadays often involve several interrelated models, which are automatically processed via a multitude of model operations. Modular and incremental construction and execution of such networks of models and model operations are required to accommodate efficient development with potentially large-scale models. The underlying problem is also called Global Model Management. In this report, we propose an approach to modular and incremental Global Model Management via an extension to the existing technique of Generalized Discrimination Networks (GDNs). In addition to further generalizing the notion of query operations employed in GDNs, we adapt the previously query-only mechanism to operations with side effects to integrate model transformation and model synchronization. We provide incremental algorithms for the execution of the resulting extended Generalized Discrimination Networks (eGDNs), as well as a prototypical implementation for a number of example eGDN operations. Based on this prototypical implementation, we experiment with an application scenario from the software development domain to empirically evaluate our approach with respect to scalability and conceptually demonstrate its applicability in a typical scenario. Initial results confirm that the presented approach can indeed be employed to realize efficient Global Model Management in the considered scenario.
This book constitutes the refereed proceedings of the 9th International Conference on Graph Transformation, ICGT 2016, held as part of STAF 2016, in Vienna, Austria, in July 2016. The 14 papers presented in this were carefully reviewed and selected from 33 submissions. They were organized in topical sections named: foundations, tools and algorithms, queries, and applications. The book also contains one keynote paper in full paper length. The book is dedicated to Hartmut Ehrig, one of the fathers and most productive members of the Graph Transformation community, who passed away in 2016. An obituary is included in the front matter of the volume.
This book constitutes the refereed proceedings of the 16th International Conference on Graph Transformation, ICGT 2023, held as Part of STAF 2023 in Leicester, UK, in July 2023. The 14 full papers and 2 short papers presented in this book were carefully reviewed and selected from 29 submissions. The conference focuses on describing new unpublished contributions in the theory and applications of graph transformation as well as tool presentation papers that demonstrate main new features and functionalities of graph-based tools.
This book constitutes the refereed proceedings of the 14th International Conference on Graph Transformation, ICGT 2021, which took place virtually during June 24-25, 2021. The 14 full papers and 2 tool papers presented in this book were carefully reviewed and selected from 26 submissions. They deal with the following topics: theoretical advances; application domains; and tool presentations.
This book constitutes the refereed proceedings of the 12th International Conference on Graph Transformation, ICGT 2019, held as part of STAF 2019, in Eindhoven, The Netherlands, in July2019. The 12 research papers and 1 tool paper presented in this book were carefully reviewed and selected from 22 submissions. The papers deal with the following topics: Theory, Analysis and Verification, Tools and Applications, and Transformation Rules Construction and Matching.
This book is Open Access under a CC BY licence. This book constitutes the proceedings of the 22nd International Conference on Fundamental Approaches to Software Engineering, FASE 2019, which took place in Prague, Czech Republic in April 2019, held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019.The 24 papers presented in this volume were carefully reviewed and selected from 94 submissions. The papers are organized in topical sections named: software verification; model-driven development and model transformation; software evolution and requirements engineering; specification, design, and implementation of particular classes of systems; and software testing.
Today, software has become an intrinsic part of complex distributed embedded real-time systems. The next generation of embedded real-time systems will interconnect the today unconnected systems via complex software parts and the service-oriented paradigm. Therefore besides timed behavior and probabilistic behaviour also structure dynamics, where the architecture can be subject to changes at run-time, e.g. when dynamic binding of service end-points is employed or complex collaborations are established dynamically, is required. However, a modeling and analysis approach that combines all these necessary aspects does not exist so far. To fill the identified gap, we propose Probabilistic Timed Graph Transformation Systems (PTGTSs) as a high-level description language that supports all the necessary aspects of structure dynamics, timed behavior, and probabilistic behavior. We introduce the formal model of PTGTSs in this paper and present a mapping of models with finite state spaces to probabilistic timed automata (PTA) that allows to use the PRISM model checker to analyze PTGTS models with respect to PTCTL properties.
Developing large software projects is a complicated task and can be demanding for developers. Continuous integration is common practice for reducing complexity. By integrating and testing changes often, changesets are kept small and therefore easily comprehensible. Travis CI is a service that offers continuous integration and continuous deployment in the cloud. Software projects are build, tested, and deployed using the Travis CI infrastructure without interrupting the development process. This report describes how Travis CI works, presents how time-driven, periodic building is implemented as well as how CI data visualization can be done, and proposes a way of dealing with dependency problems.
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 firstorder 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.