Using formal concept analysis for the verification of process-data matrices in conceptual domain models.

One of the first steps in a software engineering process is the elaboration of the conceptual domain model. In this paper, we investigate how Formal Concept Analysis can be used to formally underpin the construction of a conceptual domain model. In particular, we demonstrate that intuitive verification rules for process-data matrices can be formally grounded in FCA theory. As a case study, we show that the well-formedness rules from MERODE are isomorphic to the clustering rules in Formal Concept Analysis, and that the relationships in the class diagram are isomorphic to the subconcept-superconcept relationship in FCA.Formal concept analysis; MERODE; Conceptual domain modeling; OOSSADM; CRUD;

Reflective Composition: the declarative composition of roles to unify objects, roles, and aspects [poster session]

As bases for object-orientation, both class-based and prototype-based organization have limitations. We argue that roles have significant benefits as a foundation for organizing objects. We further argue that these benefits can be realised most flexibly using logic meta-programming. Additional benefits from this approach are to reduce redundancy and subsume aspects

Design of a Multidimensional Model Using Object Oriented Features in UML

A data warehouse is a single repository of data which includes data generated from various operational systems. Conceptual modeling is an important concept in the successful design of a data warehouse. The Unified Modeling Language (UML) has become a standard for object modeling during analysis and design steps of software system development. The paper proposes an object oriented approach to model the process of data warehouse design. The hierarchies of each data element can be explicitly defined, thus highlighting the data granularity. We propose a UML multidimensional model using various data sources based on UML schemas. We present a conceptual-level integration framework on diverse UML data sources on which OLAP operations can be performed. Our integration framework takes into account the benefits of UML (its concepts, relationships and extended features) which is more close to the real world and can model even the complex problems easily and accurately. Two steps are involved in our integration framework. The first one is to convert UML schemas into UML class diagrams. The second is to build a multidimensional model from the UML class diagrams. The white-paper focuses on the transformations used in the second step. We describe how to represent a multidimensional model using a UML star or snowflake diagram with the help of a case study. To the best of our knowledge, we are the first people to represent a UML snowflake diagram that integrates heterogeneous UML data sources

Complexity Metrics for Systems Development Methods and Techniques

So many systems development methods have been introduced in the last decade that one can talk about a ¿methodology jungle¿. To aid the method developers and evaluators in fighting their way through this jungle, we propose a systematic approach for measuring properties of methods. We describe two sets of metrics which measure the complexity of single diagram techniques, and of complete systems development methods. The proposed metrics provide a relatively fast and simple way to analyse the descriptive capabilities of a technique or method. When accompanied with other selection criteria, the metrics can be used for estimating the relative complexity of a technique compared to others. To demonstrate the applicability of the metrics, we have applied them to 36 techniques and 11 methods