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Formal Dependability Modeling and Analysis: A Survey

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9791))

Abstract

Dependability is an umbrella concept that subsumes many key properties about a system, including reliability, maintainability, safety, availability, confidentiality, and integrity. Various dependability modeling techniques have been developed to effectively capture the failure characteristics of systems over time. Traditionally, dependability models are analyzed using paper-and-pencil proof methods and computer based simulation tools but their results cannot be trusted due to their inherent inaccuracy limitations. The recent developments in probabilistic analysis support using formal methods have enabled the possibility of accurate and rigorous dependability analysis. Thus, the usage of formal methods for dependability analysis is widely advocated for safety-critical domains, such as transportation, aerospace and health. Given the complementary strengths of mainstream formal methods, like theorem proving and model checking, and the variety of dependability models judging the most suitable formal technique for a given dependability model is not a straightforward task. In this paper, we present a comprehensive review of existing formal dependability analysis techniques along with their pros and cons for handling a particular dependability model.

The original version of this chapter was revised. The spelling of the author Waqar Ahmad has been corrected. The erratum to this chapter is available at DOI: 10.1007/978-3-319-42547-4_13

An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-42547-4_13

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Acknowledgments

This publication was made possible by NPRP grant # [5 - 813 - 1 - 134] from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the author[s].

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Ahmad, W., Hasan, O., Tahar, S. (2016). Formal Dependability Modeling and Analysis: A Survey. In: Kohlhase, M., Johansson, M., Miller, B., de Moura, L., Tompa, F. (eds) Intelligent Computer Mathematics. CICM 2016. Lecture Notes in Computer Science(), vol 9791. Springer, Cham. https://doi.org/10.1007/978-3-319-42547-4_10

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