Improving the Accuracy of Defect Diagnosis with Multiple Sets of Candidate Faults.

Given a chip that produced a faulty output response to a test set, a defect diagnosis procedure produces a set of candidate faults that is expected to identify the defects that are present in the chip. The accuracy of the set of candidate faults is higher when the set is smaller or when its overlap with the defects that are present in the chip is larger. To increase the accuracy of a set of candidate faults, this paper describes an approach where several sets of candidate faults are computed based on different subsets of the test set. The subsets are obtained by removing small numbers of tests from the complete test set. The result is sets of candidate faults that are similar but not identical. The number of sets where a fault appears yields a confidence level that the fault actually belongs in a set of candidate faults. New sets of candidate faults are defined based on the confidence levels obtained. The smallest set of candidate faults can be used as the final result of defect diagnosis, or the sets can be used for ranking the candidates. Experimental results for benchmark circuits demonstrate the effectiveness of this approach. [ABSTRACT FROM PUBLISHER]