Point and expected interval availability analysis with stationarity detection

Interval availability is a dependability measure defined by the fraction of time during which a system is in operation over a finite observation period. The system is assumed to be modeled by a finite Markov process. Because the computation of the distribution of this random variable is very expensive, it is common to compute only its expectation. In this note, we propose a new algorithm to compute the expected interval availability and we compare it with respect to the standard uniformization technique from an execution time point of view. This new method is particularly interesting if the Markov chain is stiff. Moreover, a new algorithm for the stationarity detection is proposed in order to avoid excessive computation.