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This paper presents a stepwise approach for dependability modeling, based on Generalized Stochastic Petri Nets (GSPNs). The first-step model called functional-level model, can be built as early as system functional specifications and then completed by the structural model as soon as the system architecture is known, even at a very high level. The latter can be refined according to three different aspects: Component decomposition, state and event fine-tuning and distribution adjustment to take into account increasing event rates. We define specific rules to make the successive transformations as easy and systematic as possible. This approach allows the various dependencies to be taken into account at the right level of abstraction: Functional dependency, structural dependency and those induced by non-exponential distributions. A part of the approach is applied to an instrumentation and control system (I&C) in power plants.

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