Fault tree analysis of software-controlled component systems based on second-order probabilities

Software is still mostly regarded as a black box in the development process, and its safety-related quality ensured primarily by process measures. For systems whose lion share of service is delivered by (embedded) software, process-centred methods are seen to be no longer sufficient. Recent safety norms (for example, ISO 26262) thus prescribe the use of safety models for both hardware and software. However, failure rates or probabilities for software are difficult to justify. Only if developers take good design decisions from the outset will they achieve safety goals efficiently. To support safety-oriented navigation of the design space and to bridge the existing gap between qualitative analyses for software and quantitiative ones for hardware, we propose a fault-tree-based approach to the safety analysis of softwarecontrolled systems. Assigning intervals instead of fixed values to events and using Monte-Carlo sampling, probability mass functions of failure probabilities are derived. Further analysis of PMF lead to estimates of system quality that enable safety managers to take an optimal choice between design alternatives and to target costefficient solutions in every phase of the design process.