Diagnosis of transition fault clusters

  • Authors:
  • Irith Pomeranz

  • Affiliations:
  • Purdue University, W. Lafayette, IN

  • Venue:
  • Proceedings of the 48th Design Automation Conference
  • Year:
  • 2011

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Abstract

When multiple defects are present in a chip, the defects may be distributed randomly, or clustered in certain areas. When a large number of defects are clustered in an area, the possibility that their effects will interact is stronger than when they are fewer and further apart. This paper demonstrates that this reduces the accuracy of fault diagnosis based on single faults. Specifically, with the same diagnosis procedure based on single faults and the same number of faults injected into a circuit, random subsets of transition faults are easier to diagnose than clusters. The paper also develops a fault diagnosis procedure based on single faults that provides more accurate results for large clusters. The procedure considers limited numbers of double transition faults in order to obtain better matches for the cluster being diagnosed.