NDLI: Finite satisfiability of class diagrams: practical occurrence and scalability of the FiniteSat algorithm

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Finite satisfiability of class diagrams: practical occurrence and scalability of the FiniteSat algorithm

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Finite satisfiability of class diagrams: practical occurrence and scalability of the FiniteSat algorithm

Content Provider	ACM Digital Library
Author	Balaban, Mira Jelnov, Pavel Makarenkov, Victor Maraee, Azzam
Abstract	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.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF
ISBN	9781605588766
DOI	10.1145/1656485.1656486
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-10-05
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Multiplicity constraints Statistical significance Large models Scalability Finite satisfiability occurrence Benchmarking Uml class diagram Linear programming reduction Detection
Content Type	Text
Resource Type	Article

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