Authors:
Sandra Greiner
;
Felix Schwägerl
and
Bernhard Westfechtel
Affiliation:
University of Bayreuth, Germany
Keyword(s):
Model-Driven Software Engineering, Software Product Line Engineering, Model Transformations, Variability, Organized Reuse.
Related
Ontology
Subjects/Areas/Topics:
Applications and Software Development
;
Languages, Tools and Architectures
;
Model Transformation
;
Model-Driven Architecture
;
Model-Driven Software Development
;
Models
;
Paradigm Trends
;
Software Engineering
;
Software Factories and Software Product Lines
Abstract:
Model transformations are crucial in model-driven software engineering (MDSE). While combining MDSE and software product line engineering (SPLE) techniques, summarized as model-driven product line engineering (MDPLE), promises increased productivity by relying on organized reuse, the benefits are impeded by transformation specifications designed exclusively for single-variant models. Applying single-variant model transformations to multi-variant input models results in output models lacking the variability information. Multi-variant model transformations (MVMT), which preserve variability information, have only recently been understood as an explicit research problem. In this paper, we propose an a posteriori approach towards MVMT. Following the paradigm of organized reuse, we propose to employ single-variant model transformations without modifications in a first step, and to transfer variability information afterwards based on the artifacts provided by the single-variant transformat
ion specification. In particular, we implemented this approach for the well-known model-to-model transformation language ATL. To deduce variability information, the execution artifacts (trace and execution model) are analyzed. Then, variability annotations are transfered to the target model automatically. The implementation is evaluated based on a practically example of a Graph product line. Results exhibit that our approach outperforms the conventional solution with respect to user effort, accuracy and performance.
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