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.
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References
Interim Defence Standard 00-56 Part 1 - Issue 5, in, UK MOD (2014)
Yang, J.-B., Xu, D.-L.: On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty. IEEE Transactions on Systems, Man, and Cybernetics, Part AÂ 32(3) (2002)
Nair. S, et al.: The State of the Practice on Evidence Management for Compliance with Safety Standards, Simula Research Laboratory, Techincal Report (2013)
Nair, S., et al.: An Extended Systematic Literature Review on Provision of Evidence for Safety Certification. Information and Software Technology 56(7), 689–717 (2014)
Hawkins, R., et al.: A new approach to creating clear safety arguments. In: Advances in Systems Safety, pp. 3–23 (2011)
Hamilton, V.: Criteria for Software Evidence, Goal-based standards require evidence-based approaches. Safety Systems 16, 1 (2006)
Nair. S, et al.: Understanding the practice of Safety Evidence Assessment: A Qualitative Semi-Structured Interview Study. Technical report, Simula Research Laboratory (2014)
Denney, E., Pai, G.: A lightweight methodology for safety case assembly. In: Ortmeier, F., Lipaczewski, M. (eds.) SAFECOMP 2012. LNCS, vol. 7612, pp. 1–12. Springer, Heidelberg (2012)
Weaver, R., et al.: Gaining confidence in goal-based safety cases. In: Developments in Risk-based Approaches to Safety, pp. 277–290 (2006)
Ayoub, A., Kim, B., Lee, I., Sokolsky, O.: A systematic approach to justifying sufficient confidence in software safety arguments. In: Ortmeier, F., Lipaczewski, M. (eds.) SAFECOMP 2012. LNCS, vol. 7612, pp. 305–316. Springer, Heidelberg (2012)
Denney, E., et al.: Towards measurement of confidence in safety cases. In: ESEM (2011)
Dempster, A.P.: A generalization of Bayesian inference. Journal of the Royal Statistical Society, Series B 30, 205–247 (1968)
Shafer. G.: A Mathematical Theory of Evidence. Princeton University Press (1976)
Walkinshaw. N.: Using evidential reasoning to make qualified predictions of software quality. In: PROMISE (2013)
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Nair, S., Walkinshaw, N., Kelly, T. (2014). Quantifying Uncertainty in Safety Cases Using Evidential Reasoning. In: Bondavalli, A., Ceccarelli, A., Ortmeier, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2014. Lecture Notes in Computer Science, vol 8696. Springer, Cham. https://doi.org/10.1007/978-3-319-10557-4_45
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DOI: https://doi.org/10.1007/978-3-319-10557-4_45
Publisher Name: Springer, Cham
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