Modeling and Analysis of Component Faults and Reliability

Research output: Research - peer-reviewBook chapter

Abstract

This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets that are automatically generated. The stochastic information on the faults is used to estimate the reliability of the fault affected system. The reliability is given with respect to properties of the system state space. We illustrate the process on a concrete example using the Uppaal model checker for validating the ideal system model and the fault modeling. Then the statistical version of the tool, UppaalSMC, is used to find reliability estimates.
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This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets that are automatically generated. The stochastic information on the faults is used to estimate the reliability of the fault affected system. The reliability is given with respect to properties of the system state space. We illustrate the process on a concrete example using the Uppaal model checker for validating the ideal system model and the fault modeling. Then the statistical version of the tool, UppaalSMC, is used to find reliability estimates.
Original languageEnglish
Title of host publicationFrom Action Systems to Distributed Systems : The Refinement Approach
EditorsLuigia Petre, Emil Sekerinski
PublisherC R C Press LLC
Publication dateMay 2016
Pages45-60
Chapter4
ISBN (Print)978-1-4987-0158-7
ISBN (Electronic)978-1-4987-0159-4
DOI
StatePublished - May 2016
Publication categoryResearch
Peer-reviewedYes
SeriesComputational Science Series

    Research areas

  • Reliability Analysis, model checking
ID: 233532560