• DocumentCode
    3240066
  • Title

    Physically-Aware N-Detect Test Pattern Selection

  • Author

    Lin, Yen-Tzu ; Poku, Osei ; Bhatti, Naresh K. ; Blanton, R. D Shawn

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA
  • fYear
    2008
  • fDate
    10-14 March 2008
  • Firstpage
    634
  • Lastpage
    639
  • Abstract
    N-detect test has been shown to have a higher likelihood for detecting defects. However, traditional definitions of N-detect test do not necessarily exploit the localized characteristics of defects. In physically-aware N-detect test, the objective is to ensure that the N tests establish N different logical states on the signal lines that are in the physical neighborhood surrounding the targeted fault site. We present a test selection procedure for creating a physically- aware N-detect test set that satisfies a user-provided constraint on test-set size. Results produced for an industrial test chip demonstrate the effectiveness and practicability of our pattern selection approach. Specifically, we show that we can virtually detect the same number of faults 10 or more times as a traditional 10-detect test set and increase the number of neighborhood states and the number of faults with 10 or more states by 18.0 and 4.7%, respectively, without increasing the number of tests over a traditional 10-detect test set.
  • Keywords
    automatic test pattern generation; fault diagnosis; logic testing; N different logical states; fault detection; industrial test chip; physical neighborhood; physically-aware N-detect test pattern selection; signal lines; test-set size; user-provided constraint; Automatic test pattern generation; Automatic testing; Circuit faults; Circuit testing; Complexity theory; Fault detection; Logic circuits; Logic testing; Test pattern generators; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design, Automation and Test in Europe, 2008. DATE '08
  • Conference_Location
    Munich
  • Print_ISBN
    978-3-9810801-3-1
  • Electronic_ISBN
    978-3-9810801-4-8
  • Type

    conf

  • DOI
    10.1109/DATE.2008.4484748
  • Filename
    4484748