Model transformations are considered to be the "heart" and "soul" of Model Driven Engineering, and as a such, advanced techniques and tools are needed for supporting the development, quality assurance, maintenance, and evolution of model transformations. Even though model transformation developers are gaining the availability of powerful languages and tools for developing, and testing model transformations, very few techniques are available to support the understanding of transformation characteristics. In this paper, we propose a process to analyze model transformations with the aim of identifying to what extent their characteristics depend on the corresponding input and target metamodels. The process relies on a number of transformation and metamodel metrics that are calculated and properly correlated. The paper discusses the application of the approach on a corpus consisting of more than 90 ATL transformations and 70 corresponding metamodels.

Mining correlations of ATL model transformation and metamodel metrics

DI ROCCO, JURI;DI RUSCIO, DAVIDE;IOVINO, LUDOVICO;PIERANTONIO, ALFONSO
2015-01-01

Abstract

Model transformations are considered to be the "heart" and "soul" of Model Driven Engineering, and as a such, advanced techniques and tools are needed for supporting the development, quality assurance, maintenance, and evolution of model transformations. Even though model transformation developers are gaining the availability of powerful languages and tools for developing, and testing model transformations, very few techniques are available to support the understanding of transformation characteristics. In this paper, we propose a process to analyze model transformations with the aim of identifying to what extent their characteristics depend on the corresponding input and target metamodels. The process relies on a number of transformation and metamodel metrics that are calculated and properly correlated. The paper discusses the application of the approach on a corpus consisting of more than 90 ATL transformations and 70 corresponding metamodels.
9781479919345
9781479919345
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/107914
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