Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/89202
Título: | Merging cloned Alloy models with colorful refactorings |
Autor(es): | Liu, Chong Macedo, Nuno Cunha, Alcino |
Palavras-chave: | Alloy Clone-and-own Feature-oriented design Model merging Refactoring |
Data: | 2022 |
Editora: | Elsevier 1 |
Revista: | Science of Computer Programming |
Citação: | Liu, C., Macedo, N., & Cunha, A. (2022, August). Merging cloned Alloy models with colorful refactorings. Science of Computer Programming. Elsevier BV. http://doi.org/10.1016/j.scico.2022.102829 |
Resumo(s): | Likewise to code, clone-and-own is a common way to create variants of a model, to explore the impact of different features while exploring the design of a software system. Previously, we have introduced Colorful Alloy, an extension of the popular Alloy language and toolkit to support feature-oriented design, where model elements can be annotated with feature expressions and further highlighted with different colors to ease understanding. In this paper we propose a catalog of refactoring laws for Colorful Alloy models, and show how they can be used to iteratively merge cloned Alloy models into a single feature-annotated colorful model, where the commonalities and differences between the different clones are easily perceived, and more efficient aggregated analyses can be performed. We then show how these refactorings can be composed in an automated merging strategy that can be used to migrate Alloy clones into a Colorful Alloy SPL in a single step. The paper extends a conference version [1] by formalizing the semantics and type system of the improved Colorful Alloy language, allowing the simplification of some rules and the evaluation of their soundness. Additional rules were added to the catalog, and the evaluation extended. The automated merging strategy is also novel. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/89202 |
DOI: | 10.1016/j.scico.2022.102829 |
ISSN: | 0167-6423 |
Versão da editora: | https://www.sciencedirect.com/science/article/pii/S0167642322000624 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | HASLab - Artigos em revistas internacionais |
Este trabalho está licenciado sob uma Licença Creative Commons