Representing and reasoning on fuzzy UML models: A description logic approach

Abstract

0957-4174/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.eswa.2010.08.042 ⇑ Corresponding author. Tel./fax: +86 24 83681582 E-mail address: mazongmin@ise.neu.edu.cn (Z.M. UML is the most widely accepted formalism for the analysis and design of software. Recent proposals to improve the ability of reasoning automatically on UML models. However, information imprecision and uncertainty exist in many real-world applications and hence fuzzy UML models have been extensively investigated. In this paper, we propose a description logic approach to represent and reason on fuzzy UML models. Firstly, for the specific purposes of representing and reasoning on fuzzy UML models, a fuzzy description logic called FDLR (fuzzy DLR) is introduced. Moreover, we further investigate the reasoning problems and reasoning algorithms for FDLR. Then, the fuzzy UML model is investigated, and a kind of formal definition of fuzzy UML models is proposed. Furthermore, representation and reasoning of fuzzy UML models with FDLR is investigated, i.e., we first consider the fuzzy UML model and the corresponding fuzzy UML instantiations (i.e., object diagrams) simultaneously, and translate them into FDLR knowledge bases at both terminological (TBox) and assertional (ABox) levels, respectively; then how the reasoning problems of fuzzy UMLmodels (e.g., consistency, subsumption, logical consequence, and so on) may be reasoned through reasoning mechanism of FDLR is investigated. The formalization in FDLR of fuzzy UML models makes a significant improvement and it is the first step towards developing intelligent systems that provide computer aided support during the application design phase in order to automatically detect relevant properties of fuzzy UML models. 2010 Elsevier Ltd. All rights reserved.

DOI: 10.1016/j.eswa.2010.08.042

Cite this paper

@article{Ma2011RepresentingAR, title={Representing and reasoning on fuzzy UML models: A description logic approach}, author={Zongmin Ma and Fu Zhang and Li Yan and Jingwei Cheng}, journal={Expert Syst. Appl.}, year={2011}, volume={38}, pages={2536-2549} }