A Comparison of Rule Inheritance in Model-to-Model Transformation Languages

Although model transformations presumably play a major role in Model-Driven Engineering, reuse mechanisms such as inheritance have received little attention so far. In this paper, the authors propose a comparison framework for rule inheritance in declarative model-to-model transformation languages, and provide an in-depth evaluation of three prominent representatives thereof, namely ATL, ETL (declarative subsets thereof), and TGGs. The framework provides criteria for comparison along orthogonal dimensions, covering static aspects, which indicate whether a set of inheriting transformation rules is well formed at compile-time, and dynamic aspects, which describe how inheriting rules behave at run-time.

Provided by: Vienna University of Technology Topic: Big Data Date Added: Feb 2011 Format: PDF

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