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Quantifying Uncertainty in Safety Cases Using Evidential Reasoning

  • Sunil Nair
  • Neil Walkinshaw
  • Tim Kelly
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8696)

Abstract

Dealing with uncertainty is an important and difficult aspect of analyses and assessment of complex systems. A real-time large-scale complex critical system involves many uncertainties, and assessing probabilities to represent these uncertainties is itself a complex task. Currently, the certainty with which safety requirements are satisfied and the consideration of the other confidence factors often remains implicit in the assessment process. Many publications in the past have detailed the structure and content of safety cases and Goal Structured Notation (GSN). This paper does not intend to repeat them. Instead, this paper outlines a novel solution to accommodate uncertainty in the safety cases development and assessment using the Evidential-Reasoning approach - a mathematical technique for reasoning about uncertainty and evidence. The proposed solution is a bottom-up approach that first performs low-level evidence assessments that makes any uncertainty explicit, and then automatically propagates this confidence up to the higher-level claims. The solution would enable safety assessors and managers to accurately summarise their judgement and make doubt or ignorance explicit.

Keywords

safety safety assessment safety case confidence argument evidence evidential reasoning human factors expert judgement uncertainty confidence 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sunil Nair
    • 1
  • Neil Walkinshaw
    • 2
  • Tim Kelly
    • 3
  1. 1.Simula Research LaboratoryNorway
  2. 2.Department of Computer ScienceUniversity of LeicesterUnited Kingdom
  3. 3.Department of Computer ScienceUniversity of YorkUnited Kingdom

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