  Fault Tree analysis is a widely used failure analysis methodology to assess a
system in terms of safety or reliability in many industrial application
domains. However, with Fault Tree methodology there is no possibility to
express a temporal sequence of events or state-dependent behavior of
software-controlled systems. In contrast to this, Markov Chains are a
state-based analysis technique based on a stochastic model. But the use of
Markov Chains for failure analysis of complex safety-critical systems is
limited due to exponential explosion of the size of the model. In this paper,
we present a concept to integrate Markov Chains in Component Fault Tree models.
Based on a component concept for Markov Chains, which enables the association
of Markov Chains to system development elements such as components, complex or
software-controlled systems can be analyzed w.r.t. safety or reliability in a
modular and compositional way. We illustrate this approach using a case study
from the automotive domain.
