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iAF2D (incremental Automatic Functional Fault Detective) is a methodology for the identification of the faulty component in a complex system using data collected from a test session. It is an incremental approach based on a Bayesian Belief Network, where the model of the system under analysis is extracted from a faulty signature description. iAF2D reduces(More)
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