Finite satisfiability of class diagrams: Practical occurrence and scalability of the finitesat algorithm

Models lie at the heart of the emerging Model Driven Development (MDD) approach, in which software is developed by repeated transformations of models. Since models are intended as executable specifications, there is a need to provide correctness management on the model level. The underlying hypothesis of this research is that model level tools should be strengthened, to support model elements in a way that would encourage users to take advantage of their features. Furthermore, model transformations should not neglect the translation of model features. This paper explores the practical relevance of detecting Finite Satisfiability problems on the model level. The frequency of occurrence of Finite Satisfiability problems, and the scalability of the efficient FiniteSat algorithm are studied on a set of synthetic class diagrams, created along designed metrics. The contribution of this work is twofold, first in advancing towards creating a benchmark of class diagrams, and second, in the empirical study of the Finite Satisfiability problem.