Architecture-Based Reliability Evaluation under Uncertainty

The accuracy of architecture-based reliability evaluations depends on a number of parameters that need to be esti-mated, such as environmental factors or system usage. Re-searchers have tackled this problem by including uncertain-ties in architecture evaluation models and solving them ana-lytically and with simulations. The usual assumption is that the input parameter distributions are normal, and that it is sufficient to report the attributes that describe the system in terms of the mean and variance of the attribute. In this work, we introduce a simulation-based approach that can ac-commodate a diverse set of parameter range distributions, self-regulate the number of architecture evaluations to the desired significance level and reports the desired percentiles of the values which ultimately characterise a specific quality attribute of the system. We include a case study which il-lustrates the flexibility of this approach using the evaluation of system reliability