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Software Failure Probability Assessment by Bayesian Inference

Gee-Yong Park, Heung-Seop Eom, Seung Cheol Jang, Hyun Gook Kang

Nuclear Technology / Volume 183 / Number 1 / July 2013 / Pages 107-118

Technical Paper / Nuclear Plant Operations and Control / dx.doi.org/10.13182/NT13-A16996

This paper describes a method of estimating the probability of failure for trip-functioning software of a fully digitalized reactor protection system. The Bayesian inference is used to estimate and update the probability of software failure along the software development life cycle. At the requirements and design phases, the probability of software failure is estimated from qualitative quality information based on a specific verification and validation process. This probability of failure is updated at the implementation/testing phases, based on the test data for trip functions implemented by software.