Adding Rule-Based Model Transformation to Modelling Languages in MetaEdit+

Authors

  • Simon Van Mierlo University of Antwerp
  • Hans Vangheluwe McGill University Montreal

DOI:

https://doi.org/10.14279/tuj.eceasst.54.781

Abstract

MetaEdit+ is a commercial tool by MetaCase for creating domain-specific, syntax-directed visual modelling environments. MetaEdit+ synthesizes such environments from user-provided metamodels and contains a Generator Editor for code/report generation. An API is provided to allow external manipulation of models through SOAP. Currently, the MetaEdit+ tool does not natively support rule-based model-to-model transformation. Such transformations are useful as they allow domain experts to intuitively (using domain-specific notations) model either operational semantics (a simulator) or denotational semantics (through model-to-model transformation onto a model in a known formalism) of a modelling language. We will demonstrate how to add rule-based operational semantics to modelling languages in MetaEdit+. In our approach, transformation rules are visually created in MetaEdit+. The rule editor is synthesized using modified versions of the original language's metamodel. This modification is performed in a structured fashion using a process called RAMification. Both the model and the rules are exported from MetaEdit+ to Python code. This code is combined with Py-T-Core, our library of transformation language primitives, to apply the rules on the model. Our demonstration has a client-server architecture, with the MetaEdit+ visual modelling environment as the client and the transformation engine as the server. After each transformation step, in-place changes to the model are propagated to MetaEdit+ for visualization using the SOAP API. A simple (manufacturing) Production System modelling language is used as an example.

Downloads

Published

2012-11-22

How to Cite

[1]
S. Van Mierlo and H. Vangheluwe, “Adding Rule-Based Model Transformation to Modelling Languages in MetaEdit+”, eceasst, vol. 54, Nov. 2012.