On the Use of OBDDs in Model Based Diagnosis: an Approach Based on the Partition of the Model

In this paper we discuss how OBDDs (Ordered Binary Decision Diagrams) can be exploited for the computation of consistency-based diagnoses in Model-Based Diagnosis. Since it is not always possible to efficiently encode the whole system model within a single OBDD, we propose to build a set of OBDDs, each one encoding a portion of the original model. For each portion of the model, we compute an OBDD encoding the set of local diagnoses; the OBDD encoding global diagnoses is then obtained by merging all the local-diagnoses OBDDs. Finally, minimal-cardinality diagnoses can be efficiently computed and extracted.