SOFTWARE FAILURE PROBABILITY ASSESSMENT BY BAYESIAN INFERENCE

Abstract

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.