Coverage modeling for dependability analysis of fault-tolerant systems

Abstract
Several different models for predicting coverage in a fault-tolerant system, including models for permanent, intermittent, and transient errors, are discussed. Markov, semi-Markov, nonhomogeneous Markov, and extended stochastic Petri net models for computing coverage are developed. Two types of events that interfere with recovery are examined; and methods for modeling such events, whether they are deterministic or random, are given. The sensitivity of system reliability/availability to the coverage parameter and the sensitivity of the coverage parameter to various error-handling strategies are investigated. It is found that a policy of attempting transient recovery upon detection of an error (as opposed to automatically reconfiguring the affected component out of the system) can actually increase the unreliability of the system.

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