A First Experimental Evaluation of Search Plan Driven Graph Pattern Matching

Batz, Gernot Veit; Kroll, Moritz; Geiß, Rubino

doi:10.1007/978-3-540-89020-1_32

Cited by 15 publications

(3 citation statements)

References 9 publications

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“…To this end, it is necessary to detect correctly typed and attributed matches for the LHS (or pattern graph), as well as their rewriting to produce a valid result graph (H') containing the RHS (or rewrite graph) inserted. Efforts have been undertaken to significantly improve the computational complexity of match detection algorithms (Geiß et al, 2006;Batz et al, 2008). As well, a variety of rewriting methods has been researched for decades.…”

Section: Theoretical Specificationsmentioning

confidence: 99%

Graph Rewriting Techniques in Engineering Design

Kolbeck

Vilgertshofer

Abualdenien

et al. 2022

Front. Built Environ.

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Capturing human knowledge underlying the design and engineering of products has been among the main goals of computational engineering since its very beginning. Over the last decades, various approaches have been proposed to tackle this objective. Among the most promising approaches is the application of graph theory for representing product structures by defining nodes representing entities and edges representing relations among them. The concrete meaning of these structures ranges from geometry representations over hierarchical product breakdowns to functional descriptions and flows of information or resources. On top of these graph structures, graph rewriting techniques provide another powerful layer of technology. By enabling the formal definition of rules for transforming graph structures, they allow on the one hand side to formally capture the engineering development process. On the other hand, the assembly of rewriting rules into graph grammars allows for an exhaustive search of the solution space of the engineering problem at hand. In combination with search strategies, an automated optimization of the design under given constraints and objectives can be realized. The paper provides an overview of the current state-of-the-art in graph rewriting and its applications in engineering design, with a focus on the built environment. It concludes with a discussion of the progress achieved and the missing research gaps.

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Section: Theoretical Specificationsmentioning

confidence: 99%

Graph Rewriting Techniques in Engineering Design

Kolbeck

Vilgertshofer

Abualdenien

et al. 2022

Front. Built Environ.

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“…There is a line of research mainly focusing on improving the transformation engine, that executes transformations e.g., G. Varró et al 2015;Boronat 2018;Vizhanyo et al 2004;Giese et al 2009;Veit Batz et al 2008. Such works try to improve the performance by improving the algorithms within the engine.…”

Section: Related Workmentioning

confidence: 99%

A Survey on the Relevance of the Performance of Model Transformations.

Groner¹,

Juhnke²,

Götz³

et al. 2021

JOT

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In Model-Driven Engineering (MDE) model transformation languages are used to describe important operations on models.Such domain-specific languages are specially developed to describe transformation rules, according to which an output model should be generated from an input model. In comparison to these domain-specific languages, techniques to analyze and improve the performance of programs written in a general-purpose language, such as Java or C, are well known. However, are such techniques also needed for model transformation languages? Problem. Since these languages are only used in certain domains; the first question is whether performance is at all relevant for model transformations and whether techniques similar to those used to analyze and improve the performance of general-purpose languages are needed. Research in the performance of model transformations focuses mainly on comparing the performance of different languages or different definition styles or optimizing the engine that executes the transformation. However, it is not clear to what extent these efforts can mitigate or prevent performance issues, and there is also a lack of studies that examine to what extend the performance of transformations is relevant. Method. In order to close this gap and to answer the initial question about the relevance of performance, we conducted an online survey. For this purpose, we developed a questionnaire and identified 649 authors as potential participants based on a Systematic Literature Review (SLR) on a selection of model transformation languages. Additionally, we were able to acquire four further potential participants by advertising our study. In total, 84 participants took part in our survey. We used statistical tests such as Kendall's τ c , the Kruskal-Wallis-Test and the Mann-Whitney-U-Test to evaluate our hypotheses on relevant factors for the performance of model transformations. Results. The results show that specific performance is desired and that there is a willingness to improve performance. In this regard, we identified a need for insights necessary to better understand how a transformation is performed in order to be able to improve its performance. Furthermore, we investigated with the help of hypotheses tests the possible influencing factors that cause participants to try to analyze or improve the performance of model transformations. The main results of the hypotheses tests are that the satisfaction with the execution time, the size of the models used, the relevance of whether a specific execution time is not exceeded in the average case, and the knowledge of how a transformation engine executes a transformation are relevant factors.

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“…The CDTrans transformation language is accompanied with a generator that takes a transformation as input and generates a Java class that is able to execute the transformation. The generated Java class realizes the pattern matching for the pattern part of the transformation using a search plan based pattern matching approach [28], [29] and in case a match has been found applies the changes described by the transformation. This workflow from creating a transformation to applying it is depicted as an activity diagram in Fig.…”

Section: Applying a Cdtrans Transformationmentioning

confidence: 99%

Systematically deriving domain-specific transformation languages

Hölldobler

Rumpe

Weisemöller

2015

2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS)

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Abstract-Model transformations are helpful to evolve, refactor, refine and maintain models. While domain-specific languages are normally intuitive for modelers, common model transformation approaches (regardless of whether they transform graphical or textual models) are based on the modeling language's abstract syntax requiring the modeler to learn the internal representation of the model to describe transformations. This paper presents a process that allows to systematically derive a textual domainspecific transformation language from the grammar of a given textual modeling language. As example, we apply this systematic derivation to UML class diagrams to obtain a domain-specific transformation language called CDTrans. CDTrans incorporates the concrete syntax of class diagrams which is already familiar to the modeler and extends it with a few transformation operators. To demonstrate the usefulness of the derived transformation language, we describe several refactoring transformations.

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A First Experimental Evaluation of Search Plan Driven Graph Pattern Matching

Cited by 15 publications

References 9 publications

Graph Rewriting Techniques in Engineering Design

Graph Rewriting Techniques in Engineering Design

A Survey on the Relevance of the Performance of Model Transformations.

Systematically deriving domain-specific transformation languages

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