• DocumentCode
    874973
  • Title

    Defect level estimation of circuit testing using sequential statistical analysis

  • Author

    Jone, Wen-Ben

  • Author_Institution
    Dept. of Comput. Sci., New Mexico Inst. of Min. & Technol., Socorro, NM, USA
  • Volume
    12
  • Issue
    2
  • fYear
    1993
  • fDate
    2/1/1993 12:00:00 AM
  • Firstpage
    336
  • Lastpage
    348
  • Abstract
    Sequential statistical analysis is applied to determine the defect level of random and pseudorandom testing. Results derived using worst-case analysis show that the defect of pseudorandom testing is always no larger than the defect of random testing. It is found that the defect level of random testing is a good approximation of that of pseudorandom testing only if either the yield or circuit detectability is high. The random test length is estimated, using the defect level as a basis. It is shown that random test length determination based on defect level yields a more realistic result than that based on escape probability. Monte Carlo simulation is also conducted to evaluate the performance and feasibility of the proposed defect level analysis. The results obtained are based primarily on the worst-case analysis. However, the analysis also provides an exact solution if each fault occurs equally likely (a general assumption). In addition, the approach may lead to a general solution
  • Keywords
    Monte Carlo methods; integrated circuit testing; statistical analysis; Monte Carlo simulation; circuit testing; defect level analysis; pseudorandom testing; random testing; sequential statistical analysis; worst-case analysis; Bridge circuits; Circuit faults; Circuit testing; Equations; Manufacturing processes; Performance analysis; Probability; Sequential analysis; Statistical analysis; Vehicle detection;
  • fLanguage
    English
  • Journal_Title
    Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0070
  • Type

    jour

  • DOI
    10.1109/43.205012
  • Filename
    205012