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Mapping Features to Models: A Template Approach Based on Superimposed Variants

  • Krzysztof Czarnecki
  • Michał Antkiewicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3676)

Abstract

Although a feature model can represent commonalities and variabilities in a very concise taxonomic form, features in a feature model are merely symbols. Mapping features to other models, such as behavioral or data specifications, gives them semantics. In this paper, we propose a general template-based approach for mapping feature models to concise representations of variability in different kinds of other models. We show how the approach can be applied to UML 2.0 activity and class models and describe a prototype implementation.

Keywords

Activity Diagram Software Product Line Boolean Formula Decision Node Disjunctive Normal Form 
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-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Krzysztof Czarnecki
    • 1
  • Michał Antkiewicz
    • 1
  1. 1.University of WaterlooCanada

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