Towards a Decision Making Framework for Model Transformation Languages

Model transformations play increasingly important role in Model Driven Engineering (MDE). A wide variety of tools and languages are generated and released for model transformations. A challenging task of software engineer is to choose a particular model transformation language, given a set of alternatives, that is best suited for non-functional requirements of the context, which are mostly intangible and difficult to measure, if not impossible. This paper proposes a decision making framework that aids software engineer to select most proper model transformation language, given non-functional requirements (of which some are conflicting). The proposed framework is based on Fuzzy-Analytic Hierarchy Process (AHP) technique, and uses relative degree of importance of non-functional requirements for the given context in terms of fuzzy linguistic terms. The output is ranking of model transformation languages. The approach is implemented and its applicability is illustrated in three