Utilizing Device Behavior in Structure-Based Diagnosis

Structure-based approaches to diagnosis provide useful computational guarantees based on a device structure. In particular, these approaches can identify device structures for which the complexity of model-based diagnosis is guaranteed to be linear. Structure-based approaches, however, can fail to answer even the simplest diagnostic queries if the device structure is not well behaved (strongly connected). We show in this paper that this deficiency can be addressed to a reasonable extent by utilizing device behavioral properties (its component models in particular) which are typically ignored by structure-based approaches. Specifically, we present a structure-based algorithm for diagnosis which takes advantage of a device behavior and then present experimental results indicating that our algorithm can lead to significant (orders-of-magnitude) savings over pure structural approaches when applied to strongly connected devices.