• DocumentCode
    2763782
  • Title

    Enhanced DO-RE-ME based defect level prediction using defect site aggregation-MPG-D

  • Author

    Dworak, Jennifer ; Grimaila, Michael R. ; Lee, Sooryong ; Wang, Li C. ; Mercer, M. Ray

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    930
  • Lastpage
    939
  • Abstract
    Predicting the final value of the defective part level after the application of a set of test vectors is not a simple problem. In order for the defective part level to decrease, both the excitation and observation of defects must occur. This research shows that the probability of exciting an as yet undetected defect does indeed decrease exponentially as the number of observations increases. In addition, a new defective part level model is proposed which accurately predicts the final defective part level (even at high fault coverages) for several benchmark circuits and which continues to provide good predictions even as changes are made an the set of test patterns applied
  • Keywords
    automatic test pattern generation; fault diagnosis; integrated circuit testing; logic testing; ATPG; MPG-D model; benchmark circuits; defect site aggregation; defective part level; defective part level model; enhanced DO-RE-ME based defect level prediction; final defective part level; high fault coverages; test vector set; Application software; Automatic test pattern generation; Benchmark testing; Circuit faults; Circuit testing; Integrated circuit modeling; Integrated circuit testing; Logic testing; Predictive models; Test pattern generators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Test Conference, 2000. Proceedings. International
  • Conference_Location
    Atlantic City, NJ
  • ISSN
    1089-3539
  • Print_ISBN
    0-7803-6546-1
  • Type

    conf

  • DOI
    10.1109/TEST.2000.894304
  • Filename
    894304