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Towards Rule-Based Detection of Design Patterns in Model Transformations

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9959)

Abstract

Model transformations are at the very heart of the Model-Driven Engineering paradigm. As modern programs, they are complex, difficult to write and test, and overall, difficult to understand, maintain, and reuse. In other paradigms, such as object-oriented programming, design patterns play an important role for understanding and reusing code. Many works have been proposed to detect complete design pattern instances for understanding and documentation purposes, but also partial design pattern instances for quality assessment and refactoring purposes. Recently, a catalog of design patterns has been proposed for model transformations. In this paper, we propose to detect these design patterns in declarative model transformation programs. Our approach first detects the rules that may play a role in a design pattern. Then, it ensures that the control flow over these rules corresponds to the scheduling scheme in the design pattern. Our preliminary evaluation shows that our detection mechanism is effective for both complete and partial instances of design patterns.

Keywords

Design Pattern Detection Representative Part Henshin Specific Model Transformation Language Fact Templates 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.University of MontrealMontrealCanada

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