Operation Composition in Model Transformations with Complex Source Patterns

In model transformations, rules handle mapping between source metamodel elements and target metamodel elements. There are cases in which more complex structures in the source have to be selected. In some transformation languages, these complex source patterns require decomposition of trans-formation specifications into multiple rules. This decomposition negatively affects qualities of transformation specifications such as modifiability and consistency. The handling of a complex source pattern by a single transformation rule requires composition at finer granularity, i.e., operation composition. In this paper, we show how operation composition improves the quality of transformation specifications for complex source patterns. As an illustration, we implemented a complex source pattern transformation for agent systems in two well-known model transformation languages, ATL and Tefkat. ATL supports com-position at rule level, and Tefkat supports composition at operation level. We describe the requirements for transformation languages in order to support the handling of complex source patterns in single transformation rules. We discuss some transformation mechanisms that provide operation composition.

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