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The Transformation Approach to the Modelling and Evaluation of Reliability and Availability Growth

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Predictably Dependable Computing Systems

Part of the book series: ESPRIT Basic Research Series ((ESPRIT BASIC))

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Abstract

Reliability growth phenomena are not usually taken into account when performing dependability evaluations of hardware and/or software systems during their operational life. However, such phenomena are significantly important. In this paper, an approach is presented which is aimed at the modelling and evaluation of reliability and availability of systems from the knowledge of the reliability growth of their components. Section 2 is devoted to the characterization of system behavior with respect to reliability and availability. The hyperexponential model for reliability and availability growth modelling is introduced in the third section, which is then applied to multi-component systems in the fourth section. The results presented constitute a significant step towards the evaluation of reliability and availability of systems, with respect to both physical and design faults, as they enable l) reliability growth phenomena to be incorporated in hardware models, and 2) system structure to be accounted for in software models. These results are thus a contribution to a solution to the (unfortunate) current separation between hardware models and software models.

This paper is a revised version of [77].

Christian Béounes passed away on April 23, 1993.

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© 1995 ECSC — EC — EAEC, Brussels — Luxembourg

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Laprie, JC., Béounes, C., Kaâniche, M., Kanoun, K. (1995). The Transformation Approach to the Modelling and Evaluation of Reliability and Availability Growth. In: Randell, B., Laprie, JC., Kopetz, H., Littlewood, B. (eds) Predictably Dependable Computing Systems. ESPRIT Basic Research Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79789-7_22

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  • DOI: https://doi.org/10.1007/978-3-642-79789-7_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-79791-0

  • Online ISBN: 978-3-642-79789-7

  • eBook Packages: Springer Book Archive

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