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Automating Variability Model Inference for Component-Based Language Implementations

by Edoardo Vacchi, Walter Cazzola, Benoit Combemale, Mathieu Acher
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.
Reference:
Automating Variability Model Inference for Component-Based Language Implementations (Edoardo Vacchi, Walter Cazzola, Benoit Combemale, Mathieu Acher), In 18th International Software Product Line Conference (SPLC 2014) (Patrick Heymans, Julia Rubin, eds.), ACM, 2014.
Bibtex Entry:
@inproceedings{vacchi:hal-01023864,
	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.}},
	Address = {Florence, Italie},
	Author = {Vacchi, Edoardo and Cazzola, Walter and Combemale, Benoit and Acher, Mathieu},
	Booktitle = {{18th International Software Product Line Conference (SPLC 2014)}},
	Editor = {Patrick Heymans and Julia Rubin},
	Keywords = {Variability Models ; SW Product Lines ; DSL Implementation},
	Month = Sep,
	Pdf = {http://hal.inria.fr/hal-01023864/PDF/splc14-camera.pdf},
	Publisher = {ACM},
	Title = {{Automating Variability Model Inference for Component-Based Language Implementations}},
	Url = {http://hal.inria.fr/hal-01023864},
	Year = {2014},
	Bdsk-Url-1 = {http://hal.inria.fr/hal-01023864}}