The purpose of this paper is to advocate and encourage the application of fuzzy-neuro algorithms in the risk assessment of Distributed Real-Time (DRT) systems, where object-oriented and formal techniques by means of UML-SDL models are used as knowledge (data) providers to the fuzzy-neuro analyser. The paper includes an introductory description of DRT systems and the presentation of the UML and ...

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data modeling has been extensively investigated in various data models. Currently, huge amounts of electronic data are available on the Internet, and XML has been the de facto standard of information representation and exchange over the Web. This paper focuses on fuzzy XML data modeling, whic...

A number of problems may arise from architectural requirements modeling, including alignment of it with business strategy, model integration and handling the uncertain and vague information. The paper introduces a method for modeling architectural requirements in a way of ontology-based and capabilityoriented requirements elicitation. The requirements can be modeled within a three-layer framewo...

In this work, we present an application of the Fuzzy Logic in the field of prediction in Software Engineering. We specifically use the Fuzzy Prototypical Knowledge Discovery for characterizing the UML statechart diagrams according to their understandability, starting from the structural complexity and size of the diagrams, expressed by means of metrics, and the Fuzzy Deformable Prototypes, to o...

Recovering the static structure of legacy source code e.g. as an UML class diagram is quite well understood. In contrast, recovering high-level behaviour diagrams from source code is still an open issue. This paper proposes to use fuzzy pattern detection techniques for the recovery of UML collaboration diagrams from source code. The approach is based on a knowledge base of basic datatypes and o...

In the real world, data is imperfect and in various ways such as imprecision, vagueness, uncertainty, ambiguity and inconsistency. For geographic data, the fuzzy aspect is mainly manifested in time, space and the function of objects and is due to a lack of precision. Therefore, the researchers in the domain emphasize the importance of modeling data structures in GIS but also their lack of adapt...

In the real world, data is imperfect and in various ways such as imprecision, vagueness, uncertainty, ambiguity and incompleteness. For geographic data, the fuzzy aspect is mainly manifested in time, space and the function of objects and is due to a lack of precision. F-Perceptory(Zoghlami, 2013)is a recent object modeling approach for imprecise geographicdatawith UML.However,this approach does...