Optimization and Selection of Diagnosis-Oriented Fault-Insertion Points for System Test

Abstract

Hardware fault-insertion test is a promising method to diagnose functional failures and target "no trouble found (NTF)" problems in electronic systems. However, it is costly and impractical to equip all the potential fault sites with fault-insertion hardware. We present an optimization method to select the most effective outputs of a module where fault insertion logic must be placed to facilitate diagnosis. Faults inserted at the selected outputs are able to generate fault syndromes that are most similar to the errors produced by defects inside the module. This approach also ensures that the ambiguous fault candidates from other modules are maximally removed from the set of suspects. A fault syndrome is defined by the order of error occurrence at the observation points, and it is referred as an error flow. The similarity between two error flows is measured by the metric of edit distance. An integer linear programming model is used to maximize diagnostic effectiveness with a small number of fault-insertion points. Results on diagnostic accuracy for an opensource RISC highlight the effectiveness of the proposed method compared to a baseline random fault-insertion scheme.