• DocumentCode
    1360482
  • Title

    Effective Hybrid Test Program Development for Software-Based Self-Testing of Pipeline Processor Cores

  • Author

    Lu, Tai-Hua ; Chen, Chung-Ho ; Lee, Kuen-Jong

  • Author_Institution
    Dept. of Electr. Eng., Nat. Cheng-Kung Univ., Tainan, Taiwan
  • Volume
    19
  • Issue
    3
  • fYear
    2011
  • fDate
    3/1/2011 12:00:00 AM
  • Firstpage
    516
  • Lastpage
    520
  • Abstract
    This paper presents an effective hybrid test program for the software-based self-testing (SBST) of pipeline processor cores. The test program combines a deterministically developed program which explores different levels of processor core information and a block-based random program which consists of a combination of in-order instructions, random-order instructions, return instructions, as well as instruction sequences used to trigger exception/interrupt requests. Due to the complementary nature of this hybrid test program, it can achieve processor fault coverage that is comparable to the performance of the conventional scan chain method. The test response observation methods and their impacts on fault coverage are also investigated. We present the concept of micro observation versus macro observation and show that the most effective method of using SBST is through a multiple input signature register connected to the processor local bus, while conventional methods that observe only the program results in the memory lead to significantly less processor fault coverage.
  • Keywords
    microprocessor chips; pipeline processing; SBST; block-based random program; exception-interrupt requests; fault coverage; hybrid test program development; in-order instructions; instruction sequences; multiple input signature register; pipeline processor cores; random-order instructions; return instructions; scan chain method; software-based self-testing; Fault coverage measure; fault observation method; hybrid SBST; processor testing; software-based self-testing (SBST);
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/TVLSI.2009.2036184
  • Filename
    5356222