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      Formal Dependability Modeling and Analysis: A Survey

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          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.

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          NuSMV 2: An OpenSource Tool for Symbolic Model Checking

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            A comparative analysis of network dependability, fault-tolerance, reliability, security, and survivability

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              Three Chapters of Measure Theory in Isabelle/HOL

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                Author and article information

                Journal
                2016-06-22
                Article
                1606.06877
                d80befe4-a6af-4193-a7a1-7dd8cd6193bd

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                cs.SE cs.LO math.LO

                Software engineering,Theoretical computer science,Logic & Foundation
                Software engineering, Theoretical computer science, Logic & Foundation

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