• DocumentCode
    2334652
  • Title

    Genetic method for compressed skewed-load delay test generation

  • Author

    Dobai, Roland ; Balaz, Marcel

  • Author_Institution
    Inst. of Inf., Bratislava, Slovakia
  • fYear
    2012
  • fDate
    18-20 April 2012
  • Firstpage
    242
  • Lastpage
    247
  • Abstract
    Complex system-on-chips (SOCs) require low-overhead testability methods to keep the test cost at an acceptable level. Skewed-load tests seem to be the appropriate way to test delay faults in these SOCs because the test application requires only one storage element per scan cell. Compressed skewed-load test generator based on genetic algorithm is proposed for wrapper-based logic cores of SOCs. Deterministic population-initialization is used to ensure the highest achievable transition delay fault coverage for the given wrapper and scan cell order. The developed genetic algorithm performs test data compression by generating test vectors containing already overlapped test vector pairs. The experimental results show high fault coverages, decreased test lengths and better scalability in comparison to recent methods.
  • Keywords
    data compression; genetic algorithms; integrated circuit testing; system-on-chip; SOC; complex system-on-chips; compressed skewed-load delay test generation; delay fault test; deterministic population-initialization; genetic algorithm; low-overhead testability methods; scan cell order; test cost; test data compression; test vectors; transition delay fault coverage; wrapper order; wrapper-based logic cores; Biological cells; Circuit faults; Delay; Genetic algorithms; Integrated circuit modeling; System-on-a-chip; Vectors; automatic test pattern generation; genetic algorithms; skewed-load; test data compression; test length; transition delay fault;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design and Diagnostics of Electronic Circuits & Systems (DDECS), 2012 IEEE 15th International Symposium on
  • Conference_Location
    Tallinn
  • Print_ISBN
    978-1-4673-1187-8
  • Electronic_ISBN
    978-1-4673-1186-1
  • Type

    conf

  • DOI
    10.1109/DDECS.2012.6219065
  • Filename
    6219065