Abstract. Over the past years, a number of increasingly expressive languages for modelling constraint and optimisation problems have evolved. In developing a strategy to ease the complexity of building models for constraint and optimisation problems, we have asked ourselves whether, for modelling purposes, it is really necessary to introduce more new languages and notations. We have analyzed several emerging languages and formal notations and found (to our surprise) that the already existing Z notation, although not previously used in this context, proves to a high degree expressive, adaptable, and useful for the construction of problem models. To substantiate these claims, we have both compiled a large number of constraint and optimisation problems as formal Z specifications and translated models from a variety of constraint languages into Z. The results are available as an online library of model specifications, which we make openly available to the modelling community. MotivationFormal methods and notations are most commonly associated with software development in procedural and object-oriented implementation languages. We are developing a strategic software engineering approach for modelling constraint and optimisation problems (csops); one of the main underlying objectives is to integrate the notion of such problems into the standard software design cycle [8]. For this purpose, we have been investigating the use of formal notation in general and of Z in particular, coming to the conclusion that advantages are to be had in at least four areas.The first concerns the inception phase of building an initial or conceptual model. A modeller must first come up with an understanding of the problem requirements before being able to exploit its specific features. Quoting Smith, a recognized expert in the area of modelling: "Hence, although constraint programming does require an understanding of search and constraint propagation, it is by understanding the problem and building in that understanding that we can develop a successful model." [9, sec. 13] Secondly, as larger-scale software is mostly developed in a (possibly distributed) team context and problem-solving strategies are shared across the modelling community, we see the importance of formal notation as a means of communication which is not constrained by and tied to the specifics of a
This is an author produced version of a paper published in CopyrightItems in 'OpenAIR@RGU', The Robert Gordon University Open Access Institutional Repository, are protected by copyright and intellectual property law. If you believe that any material held in 'OpenAIR@RGU' infringes copyright, please contact openair-help@rgu.ac.uk with details. The item will be removed from the repository while the claim is investigated. CSP -There is more than one way to model itGerrit Renker, Hatem Ahriz and Ines AranaSchool of Computing, The Robert Gordon University Aberdeen, Scotland, UK. AbstractIn this paper, we present an approach for conceptual modelling of constraint satisfaction problems (CSP). The main objective is to achieve a similarly high degree of modelling support for constraint problems as it is already available in other disciplines. The approach uses diagrams as operational basis for the development of CSP models. To facilitate a broader scope, the use of available mainstream modelling languages is adapted. In particular, the structural aspects of the problem are visually expressed in UML, complemented by a textual representation of relations and constraints in OCL. A case study illustrates the expositions and deployment of the approach.
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