Kaninda Musumbu

Methodological Aspects of Semantics Enrichment in Model Driven Architecture

The Semantic Web is a vision for the future of the Web in which information is given explicit meaning, making it easier for machines to automatically process and integrate information available on the Web. An ontology defines the terms used to describe and represent an area of knowledge. Ontologies are used by people, databases, and applications that need to share domain information (a domain is just a specific subject area or area of knowledge, like medicine, tool manufacturing, real estate, automobile repair, financial management, etc.). In this paper we combine this two concepts to annotate models with meta-data according to the corresponding domain ontology with all the new extracted information in order to improve the performance of the entire system.

Business rules generation methods by merging model driven architecture and web semantics

The increasing complexity of the information systems must be taking into account for new technologies, and the appearance of new types of requirements raise new problems that the traditional engineering approaches of the information systems cannot always solve in an adapted way. Business Rules constitute a key element of the Semantic Web vision, allowing integration, derivation, and transformation of data from multiple sources in a distributed, transparent and scalable manner. The aim of this paper is to propose a way to automatically generate a part of the business rules by combining concepts coming from Model Driven Architecture and Semantic Web using the Ontology Definition Metamodel.

Static Checking by Means of Abstract Interpretation

Dynamic checking are usually easier to use, because the concept are established and wide well know. But they are usually limited to systems whose state space is finite. In an other part, certain faults cannot be detected dynamically, even by keeping track of the history of the state space. Indeed, the classical problem of finding the right test cases is far from trivial and limit the abilities of dynamic checkers further. Static checking have the advantage that they work on a more abstract level than dynamic checker and can verify system properties for all inputs. Problem, it is hard to assure that a violation of a modeled property corresponds to a fault in the concrete system. We propose an approach, in which we generate counter-examples dynamically using the abstract interpretation techniques.

Efficient bottom-up abstract interpretation of prolog by means of constraint solving over symbolic finite domains (extended abstract)

The subject of this paper is Abstract Interpretation of logic programs, based on Constraint Solving over Finite Domains. More specifically, we use Toupie, a Constraint language based on the μ-calculus. Fixpoint computation is the basic execution mechanism of this language. Therefore it is very convenient and efficient for Abstract Interpretation of logic programs. The following topics are covered in this paper. 1) The semantics and implementation of Toupie are described. 2) A class of abstract domains for logic programs is defined. This class can be viewed as an extension of the domain Prop ([9]) to a limited class of first order formulas with equality. It happens that the elements of this domain coincide with the objects manipulated by Toupie, i.e. 0+ formulas. 3) Transformation rules which allow the transformation of flat logic programs into Toupie programs are given. Execution of the Toupie programs on this abstract domains provides a correct bottom-up abstract interpretation of the corresponding logic programs, i.e. a complete description of the success patterns for the program. 4) An experimental evaluation of the resulting analysis tool was performed and is thoroughly described. The system was used to analyse the benchmark programs used for the same purpose in [13, 14]. Four different instances of the generic domain were evaluated: two variants of Prop and two domains for simple (but useful) type analyses. The results show that the system is very efficient and accurate on the benchmark programs. This seems to demonstrate that the proposed approach to abstract interpretation provides a versatile alternative to previous proposals for a significant class of analyses.