Substantial Fault Pair At-a-Time (SFPAT): An Automatic Diagnostic Pattern Generation Method

Volume diagnosis plays an important role in the yield learning process. To get a high quality diagnosis result, patterns with high distinguish ability are essential. However, the test patterns used by volume diagnosis commonly have low distinguish ability to specific faults. In our experiments, we observe that on average, under automatic generated test patterns, faults in the same fan out free region (FFR) account for only 6% of all possible fault pairs, but their share in total indistinguishable faults is 70%, faults in different FFRs but with the same observation points account for 4% of all fault pairs, but their share in total indistinguishable faults is 22%. Exploiting this fact that faults in the same FFRs are harder to be distinguished, we propose an Automatic Diagnostic Pattern Generation (ADPG) method named Substantial Fault Pairs at-A-Time (SFPAT)-ADPG. By applying a transformed circuit and a new fault list to an existing Automatic Test Pattern Generation (ATPG) tool, we generate the compressed test patterns which are also the diagnostic patterns with high distinguish ability for the original circuit. Experiments on ISCAS´89 and ITC´99 benchmark circuits show the effectiveness of the proposed SFPAT-ADPG method.