• DocumentCode
    1105758
  • Title

    GATTO: a genetic algorithm for automatic test pattern generation for large synchronous sequential circuits

  • Author

    Corno, Fulvio ; Prinetto, Paolo ; Rebaudengo, Maurizio ; Reorda, Matteo Soriza

  • Author_Institution
    Dipartimento di Autom. e Inf., Politecnico di Torino, Italy
  • Volume
    15
  • Issue
    8
  • fYear
    1996
  • fDate
    8/1/1996 12:00:00 AM
  • Firstpage
    991
  • Lastpage
    1000
  • Abstract
    This paper deals with automated test pattern generation for large synchronous sequential circuits and describes an approach based on genetic algorithms. A prototype system named GATTO is used to assess the effectiveness of the approach in terms of result quality and CPU time requirements. An account is also given of a distributed version of the same algorithm, named GATTO*. Being based on the PVM library, it runs on any network of workstations and is able to either reduce the required time, or improve the result quality with respect to the monoprocessor version. In the latter case, in terms of Fault Coverage, the results are the best ones reported in the literature for most of the largest standard benchmark circuits. The flexibility of GATTO enables users to easily tradeoff fault coverage and CPU time to suit their needs
  • Keywords
    automatic testing; genetic algorithms; integrated circuit testing; logic testing; sequential circuits; CPU time requirements; GATTO; PVM library; automatic test pattern generation; fault coverage; genetic algorithm; large synchronous sequential circuits; result quality; standard benchmark circuits; Automatic test pattern generation; Central Processing Unit; Circuit faults; Circuit simulation; Circuit testing; Combinational circuits; Fault diagnosis; Genetic algorithms; Sequential circuits; Test pattern generators;
  • fLanguage
    English
  • Journal_Title
    Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0070
  • Type

    jour

  • DOI
    10.1109/43.511578
  • Filename
    511578