Automating Variability Model Inference for Component-Based Language Implementations (bibtex)
@inproceedings{vacchi:hal-01023864, url = {}, title = {{Automating Variability Model Inference for Component-Based Language Implementations}}, author = {Vacchi, Edoardo and Cazzola, Walter and Combemale, Benoit and Acher, Mathieu}, abstract = {{Recently, domain-specific language development has become again a topic of interest, as a means to help designing solutions to domain-specific problems. Componentized language frameworks, coupled with variability modeling, have the potential to bring language development to the masses, by simplifying the configuration of a new language from an existing set of reusable components. However, designing variability models for this purpose requires not only a good understanding of these frameworks and the way components interact, but also an adequate familiarity with the problem domain. In this paper we propose an approach to automatically infer a relevant variability model from a collection of already implemented language components, given a structured, but general representation of the domain. We describe techniques to assist users in achieving a better understanding of the relationships between language components, and find out which languages can be derived from them with respect to the given domain.}}, keywords = {Variability Models ; SW Product Lines ; DSL Implementation}, booktitle = {{18th International Software Product Line Conference (SPLC'14)}}, publisher = {ACM}, address = {Florence, Italie}, editor = {Patrick Heymans and Julia Rubin }, year = {2014}, month = Sep, pdf = {}, }
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