Submitted: April 2017
Abstract
Fault trees are designed to capture every way a system might fail. They provide means to numerically quantify the probability of such a system failure. Commercial tools for static fault tree management and analysis have been around for several years and have reached a high level of efficiency enabling them to cope with large elaborate models, e.g. from the nuclear safety domain. Recently Hermanns et al. proposed both a more expressive formalism called static and dynamic fault trees (SDFTs) which enriches their static siblings by dynamic features, as well as efficient analysis techniques thereof. Based on this work this thesis provides an optimized command line tool for quantitative SDFT analysis along with a formal description of the underlying theory. Additionally, benchmarks of the tool’s performance on industrial size models are provided.