Building a system failure rate estimator by identifying component failure rates

Following the current trend towards the increased use of commercial off-the-shelf (COTS) components in safety-critical systems, the need arises to address safety issues related to COTS-based systems. In this paper, we introduce a hierarchical model to estimate the probability of failure, on demand, of a software system consisting of components. Thereby, available evidence on the components´ failure behaviour is combined using a Bayesian approach. An additive error term is proposed to model the changes in a component´s prior reliability once the component is transferred from the operational environment assumed by the software developer into the actual operating environment. Statistical system test data are incorporated to calculate the estimator of the system failure rate. This approach involves prior knowledge at the level where it is most likely to be available: the component level