Association for Computing Machinery
Integrated Circuit (IC) diagnosis typically analyzes failed chips by reasoning about their responses to test patterns to deduce what has gone wrong. Current trends use diagnosis as the first step in extracting valuable information from a large population of failing ICs that include, for example, design-feature failure rates and defect-occurrence statistics. However, it is difficult to examine the accuracy of these techniques because of the unavailability of sufficient fail data where such information is known. This paper describes an approach for benchmarking and verifying diagnosis techniques through failure population creation that builds on prior work in this area.