Model-based diagnosis with low-cost fault identification

In this paper, we propose an efficient algorithm for solving the posterior failure probabilities of components, which can approximate a ranking of failure probabilities for all components. When solving large-scale circuits, the time required to solve MHSs significantly affects the overall efficiency of the algorithm, making it difficult for many algorithms to return the posterior failure probabilities of components. Initially, we utilize the BAMHS algorithm combined with an incremental strategy to propose a solving framework. Subsequently, we present two important propositions for the elimination of redundant hitting sets. Finally, we provide the specific expressions for the minimization parameters.