Improving Diagnosis Through Failing Behavior Identification
Logic diagnosis analyzes the observed failing circuit responses to derive the potential defect sites. This paper describes a method for improving diagnosis through failing behavior identification (FBI). FBI captures defect behavior (i.e., activation conditions of the defect) by identifying the signal lines related to defect activation. This additional information allows the root cause to be estimated in order to improve yield, design quality, and test quality, as well as guide PFA to perform faster defect localization. FBI is accomplished by: 1) deriving the neighborhood states of the defect site, i.e., the actual values on the signal lines within logical or physical proximity to the defect site, and 2) identifying the signal lines that are most relevant to defect activation. The efficacy of FBI is validated using circuit-level and logic-level simulation experiments. The results show that FBI achieves an average accuracy of 94% in identifying signal lines that are relevant to defect activation, a 28% improvement over an existing approach. Moreover, by analyzing the neighborhood states of each defect site reported by logic diagnosis, sites that are not likely to be defective can be eliminated, which leads to improvement in diagnosis resolution. Experiment results show that with little influence on diagnosis accuracy, the number of incorrect defective sites reported by logic diagnosis can be reduced by 64%, on average.
defect behavior candidate isolation failure diagnosis ic testing multiple defect physical failure analysis