Component Composition in Business and System Modelling

Bespoke development of large business systems can be couched in terms of the composition of components, which are, put simply, chunks of development work. Design, mapping a specification to an implementation, can also be expressed in terms of components: a refinement comprising an abstract component, a concrete component and a mapping between them. Similarly, system extension is the composition of an existing component, the legacy system, with a new component, the extension. This paper overviews work being done on a UK EPSRC funded research project formulating and formalizing techniques for describing, composing and performing integrity checks on components. Although the paper focuses on the specification and development of information systems, the techniques are equally applicable to the modeling and re-engineering of businesses, where no computer system may be involved

Redevelopment of an industrial case study using Event-B and Rodin

CDIS is a commercial air traffic information system that was developed using formal methods 15 years ago by Praxis, and it is still in operation today. This system is an example of an industrial scale system that has been developed using formal methods. In particular, the functional requirements of the system were specified using VVSL -- a variant of VDM. A subset of the original specification has been chosen to be reconstructed on the Rodin platform based on the new Event-B formalism. The goal of our reconstruction was to overcome three key difficulties of the original formalisation, namely the difficulty of comprehending the original specification, the lack of any mechanical proof of the consistency of the specification and the difficulty of dealing with distribution and atomicity refinement. In this paper we elucidate how a new formal notation and tool can help to overcome these difficulties

Semantics Through Pictures: towards a diagrammatic semantics for object-oriented modelling notations

An object-oriented (OO) model has a static component, the set of allowable snapshots or system states, and a dynamic component, the set of filmstrips or sequences of snapshots. Diagrammatic notations, such as those in UML, each places constraints on the static and/or dynamic models. A formal semantics of OO modeling notations can be constructed by providing a formal description of (i) sets of snapshots and filmstrips, (ii) constraints on those sets, and (iii) the derivation of those constraints from diagrammatic notations. In addition, since constraints are contributed by many diagrams for the same model, a way of doing this compositionally is desirable. One approach to the semantics is to use first-order logic for (i) and (ii), and theory inclusion with renaming, as in Larch, to characterize composition. A common approach to (iii) is to bootstrap: provide a semantics for a kernel of the notation and then use the kernel to give a semantics to the other notations. This only works if a kernel which is sufficiently expressive can be identified, and this is not the case for UML. However, we have developed a diagrammatic notation, dubbed constraint diagrams, which seems capable of expressing most if not all static and dynamic constraints, and it is proposed that this be used to give a diagrammatic semantics to OO models

Determining the quality of mathematical software using reference data sets

This paper describes a methodology for evaluating the numerical accuracy of software that performs mathematical calculations. The authors explain how this methodology extends the concept of metrological traceability, which is fundamental to measurement, to include software quality. Overviews of two European Union-funded projects are also presented. The first project developed an infrastructure to allow software to be verified by testing, via the internet, using reference data sets. The primary focus of the project was software used within systems that make physical measurements. The second project, currently underway, explores using this infrastructure to verify mathematical software used within general scientific and engineering disciplines. Publications on using reference data sets for the verification of mathematical software are usually intended for a readership specialising in measurement science or mathematics. This paper is aimed at a more general readership, in particular software quality specialists and computer scientists. Further engagement with experts in these disciplines will be helpful to the continued development of this application of software quality

Interpreting the Object Constraint Language

The Object Constraint Language (OCL), which forms part of the UML 1.1. set of modelling notations is a precise, textual language for expressing constraints that cannot be shown in the standard diagrammatic notation used in UML. A semantics for OCL lays the foundation for building CASE tools that support integrity checking of the whole UML models, not just the component expressed using OCL. This paper provides a semantics for OCL, at the same time providing a semantics for classes, associations, attributes and states