Extracting sbvr business vocabularies from uml use case models using m2m transformations based on drag-and-drop actions

Abstract

In the domain of model-driven system engineering, model-to-model (M2M) transformations present a very relevant topic because they may provide much-needed automation capabilities to the whole CASE-supported system development life cycle. Nonetheless, it is observed that throughout the whole development process M2M transformations are spread unevenly; in this respect, the phases of Business Modeling and System Analysis are arguably the most underdeveloped ones. The main novelty and contributions of this paper are the presented set of model-based transformations for extracting well-structured SBVR business vocabularies from visual UML use case models, which utilizes M2M transformation technology based on the so-called drag-and-drop actions. The conducted experiments show that this new development provides the same transformation power while introducing more flexibility to the model development process as compared to our previously developed approach for (semi-)automatic extraction of SBVR business vocabularies from UML use case models.