Abstract
Fault trees theories have been used in years because they can easily provide a concise representation of failure behavior of general non-repairable fault-tolerant systems. But the defect of traditional fault trees is lack of accuracy when modeling sequence-dependent dynamic failure behavior of certain systems with fault-recovery process. A solution to this problem is called behavioral decomposition. A system will be divided into several dynamic or static modules, and each module can be further analyzed using BDD or Markov Chains separately. In this paper, we will show a decomposition scheme that independent subtrees of a dynamic module are detected and solved hierarchically for saving computation time of solving Markov Chains by reducing the state space of Markov model but without losing unacceptable accuracy when assessing components sensitivities. In the end, we present our analyzing software toolkit: DyFA (Dynamic Fault-trees Analyzer) which implements our enhanced methodology.