Model-driven engineering involves the construction of models on different levels of abstraction. Software engineers are supported by model transformations, which automate the transition from high- to low-level models. Product line engineering denotes a systematic process that aims at developing different product variants from a set of reusable assets. When model-driven engineering is combined with product line engineering, engineers have to deal with multi-variant models. In annotative approaches to product line engineering, model elements are decorated with annotations, i.e., Boolean expressions that define the product variants in which model elements are to be included. In model-driven product line engineering, domain engineers require multi-variant transformations, which create multi-variant target models from multi-variant source models. We propose a reuse-based gray-box approach to realizing multi-variant model transformations. We assume that single-variant transformations already exist, which have been developed for model-driven engineering, without considering product lines. Furthermore, we assume that single-variant transformations create traces, which comprise the steps executed in order to derive target models from source models. Single-variant transformations are extended into multi-variant transformations by trace-based propagation: after executing a single-variant transformation, the resulting single-variant target model is enriched with annotations that are calculated with the help of the transformation’s trace. This approach may be applied to single-variant transformations written in different languages and requires only access to the trace, not to the respective transformation definition. We also provide a correctness criterion for trace-based propagation, and a proof that this criterion is satisfied under the prerequisites of a formal computational model.
CITATION STYLE
Westfechtel, B., & Greiner, S. (2020). Extending single- to multi-variant model transformations by trace-based propagation of variability annotations. Software and Systems Modeling, 19(4), 853–888. https://doi.org/10.1007/s10270-020-00791-9
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