ABSTRACT
In this chapter, the authors outline ways of assessing the reliability of complex systems in terms of both their component failure behavior and also in terms of the extent to which they contain design defects. They show how Bayesian networks (BN) can be used to model systems' reliability, from failure data collected during test or operation, to predict future systems' reliability or to diagnose faults in such systems. The authors also show how they can take account of the structure of the system in the analysis, especially the fault tolerance, redundancy, and other reliability enhancing methods used in the design. They give an example of system fault monitoring using a dynamic BN to monitor or control a working system. The authors discuss the role of defect modeling, with an emphasis on defects in software, but given that software is the embodiment of design, the ideas covered here are just as relevant to all design artifacts regardless of their physical embodiment.
