Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/13252
Título: A framework for efficient model transformations
Autor: Gomes, Cláudio Ângelo Gonçalves
Orientador: Amaral, Vasco
Barroca, Bruno
Palavras-chave: Model transformations
DSL
Language design
Pattern matching
Model transformation optimization
Model-driven development
Data de Defesa: Set-2013
Resumo: The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.
URI: http://hdl.handle.net/10362/13252
Designação: Dissertação
Aparece nas colecções:FCT: DI - Dissertações de Mestrado

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