Modularizing Triple Graph Grammars Using Rule Refinement
Model transformation plays a central role in Model-Driven Engineering. In application scenarios such as tool integration or view specification, bidirectionality is a crucial requirement. Triple Graph Grammars (TGGs) are a formally founded, bidirectional transformation language, which has been used successfully in various case studies from different applications domains.
In practice, supporting the maintainability of TGGs is a current challenge and existing modularity concepts, e.g., to avoid pattern duplication in TGG rules, are still inadequate. Existing TGG tools either provide no support at all for modularity, or provide limited support with restrictions that are often not applicable.
In this paper, we present and formalize a novel modularity concept for TGGs: Rule refinement, which generalizes existing modularity concepts, solves the problem of pattern duplication, and enables concise, maintainable specifications.
Keywordsmodel transformation triple graph grammars modularity
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