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Approximation Space for Software Models

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Transactions on Rough Sets I

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 3100))

Abstract

This article introduces an approximation space for graded acceptance of proposed software models for system design relative to design patterns that conform to a system design standard. A fundamental problem in system design is that feature values extracted from experimental design models tend not to match exactly patterns associated with standard design models. It is not generally known how to measure the extent that a particular system design conforms to a standard design pattern. The rough set approach introduced by Zdzislaw Pawlak provides a ground for concluding to what degree a particular model for a system design is a part of a set of a set of models representing a standard. To some extent, this research takes into account observations made by Christopher Alexander about the idea of form in Plato’s philosophy, which is helpful in arriving at an understanding about design patterns used to classify similar models for system designs. The basic assumption made in this research is that every system design can be approximated relative to a standard, and it is possible to prescribe conditions for the construction of a set of acceptable software models. The template method and memento behavioral design patterns are briefly considered by way of illustration. An approximation space for software models is introduced. In addition, an approach to the satisfaction- based classification of software models is also presented.

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Peters, J.F., Ramanna, S. (2004). Approximation Space for Software Models. In: Peters, J.F., Skowron, A., Grzymała-Busse, J.W., Kostek, B., Świniarski, R.W., Szczuka, M.S. (eds) Transactions on Rough Sets I. Lecture Notes in Computer Science, vol 3100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27794-1_16

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  • DOI: https://doi.org/10.1007/978-3-540-27794-1_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22374-0

  • Online ISBN: 978-3-540-27794-1

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