Evaluation of Kermeta for Solving Graph-based Problems

Kermeta is a meta-language for specifying the structure and behavior of graphs of interconnected objects called models. In this paper,\ud we show that Kermeta is relatively suitable for solving three graph-based\ud problems. First, Kermeta allows the specification of generic model\ud transformations such as refactorings that we apply to different metamodels\ud including Ecore, Java, and Uml. Second, we demonstrate the extensibility\ud of Kermeta to the formal language Alloy using an inter-language model\ud transformation. Kermeta uses Alloy to generate recommendations for\ud completing partially specified models. Third, we show that the Kermeta\ud compiler achieves better execution time and memory performance compared\ud to similar graph-based approaches using a common case study. The\ud three solutions proposed for those graph-based problems and their\ud evaluation with Kermeta according to the criteria of genericity,\ud extensibility, and performance are the main contribution of the paper.\ud Another contribution is the comparison of these solutions with those\ud proposed by other graph-based tools

Ludo: A Case Study for Graph Transformation Tools

In this paper we describe the Ludo case, one of the case studies of the AGTIVE 2007 Tool Contest (see [22]). After summarising the case description, we give an overview of the submitted solutions. In particular, we propose a number of dimensions along which choices had to be made when solving the case, essentially setting up a solution space; we then plot the spectrum of solutions actually encountered into this solution space. In addition, there is a brief description of the special features of each of the submissions, to do justice to those aspects that are not distinguished in the general solution space

GMF: A Model Migration Case for the Transformation Tool Contest

Using a real-life evolution taken from the Graphical Modeling Framework, we invite submissions to explore ways in which model transformation and migration tools can be used to migrate models in response to metamodel adaptation.Comment: In Proceedings TTC 2011, arXiv:1111.440

A Solution to the Flowgraphs Case Study using Triple Graph Grammars and eMoflon

After 20 years of Triple Graph Grammars (TGGs) and numerous actively maintained implementations, there is now a need for challenging examples and success stories to show that TGGs can be used for real-world bidirectional model transformations. Our primary goal in recent years has been to increase the expressiveness of TGGs by providing a set of pragmatic features that allow a controlled fallback to programmed graph transformations and Java. Based on the Flowgraphs case study of the Transformation Tool Contest (TTC 2013), we present (i) attribute constraints used to express complex bidirectional attribute manipulation, (ii) binding expressions for specifying arbitrary context relationships, and (iii) post-processing methods as a black box extension for TGG rules. In each case, we discuss the enabled trade-off between guaranteed formal properties and expressiveness. Our solution, implemented with our metamodelling and model transformation tool eMoflon (www.emoflon.org), is available as a virtual machine hosted on Share.Comment: In Proceedings TTC 2013, arXiv:1311.753

Saying Hello World with GReTL - A Solution to the TTC 2011 Instructive Case

This paper discusses the GReTL solution of the TTC 2011 Hello World case. The submitted solution covers all tasks including the optional ones.Comment: In Proceedings TTC 2011, arXiv:1111.440

Solving the TTC 2011 Reengineering Case with GrGen.NET

The challenge of the Reengineering Case is to extract a state machine model out of the abstract syntax graph of a Java program. The extracted state machine offers a reduced view on the full program graph and thus helps to understand the program regarding the question of interest. We tackle this task employing the general purpose graph rewrite system GrGen.NET (www.grgen.net).Comment: In Proceedings TTC 2011, arXiv:1111.440

Solving the TTC 2011 Reengineering Case with GReTL

This paper discusses the GReTL reference solution of the TTC 2011 Reengineering case. Given a Java syntax graph, a simple state machine model has to be extracted. The submitted solution covers both the core task and the two extension tasks.Comment: In Proceedings TTC 2011, arXiv:1111.440

Modelling and Analysis Using GROOVE

In this paper we present case studies that describe how the graph transformation tool GROOVE has been used to model problems from a wide variety of domains. These case studies highlight the wide applicability of GROOVE in particular, and of graph transformation in general. They also give concrete templates for using GROOVE in practice. Furthermore, we use the case studies to analyse the main strong and weak points of GROOVE

Distributed graph-based state space generation

LTSMIN provides a framework in which state space generation can be distributed easily over many cores on a single compute node, as well as over multiple compute nodes. The tool works on the basis of a vector representation of the states; the individual cores are assigned the task of computing all successors of states that are sent to them. In this paper we show how this framework can be applied in the case where states are essentially graphs interpreted up to isomorphism, such as the ones we have been studying for GROOVE. This involves developing a suitable vector representation for a canonical form of those graphs. The canonical forms are computed using a third tool called BLISS. We combined the three tools to form a system for distributed state space generation based on graph grammars. We show that the time performance of the resulting system scales well (i.e., close to linear) with the number of cores. We also report surprising statistics on the memory\ud consumption, which imply that the vector representation used to store graphs in LTSMIN is more compact than the representation used in GROOVE