• DocumentCode
    1853129
  • Title

    Addressing false causality while detecting predicates in distributed programs

  • Author

    Tarafdar, Ashis ; Garg, Vijay K.

  • Author_Institution
    Dept. of Comput. Sci., Texas Univ., Austin, TX, USA
  • fYear
    1998
  • fDate
    26-29 May 1998
  • Firstpage
    94
  • Lastpage
    101
  • Abstract
    The partial-order model of distributed computations based on the happened before relation has been criticized for allowing false causality between events. Our strong causality model addresses this problem by allowing multiple local threads of control. This paper addresses the predicate detection problem for the class of weak conjunctive predicates in the strong causality model. We show that, in general, the problem is NP-complete. However, an efficient solution is demonstrated for a useful sub-case. Further, this solution can be used to achieve an exponential reduction in time for solving the general problem. Our predicate detection algorithms can be applied to distributed debugging when processes have independent events, as in multi-threaded processes
  • Keywords
    computational complexity; distributed processing; parallel programming; program debugging; NP-complete; distributed computations; distributed debugging; distributed programs; false causality; multi-threaded processes; multiple local threads of control; partial-order model; predicate detection problem; strong causality model; weak conjunctive predicates; Computational modeling; Concurrent computing; Debugging; Detection algorithms; Distributed computing; Educational programs; Event detection; Processor scheduling; Testing; Yarn;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing Systems, 1998. Proceedings. 18th International Conference on
  • Conference_Location
    Amsterdam
  • ISSN
    1063-6927
  • Print_ISBN
    0-8186-8292-2
  • Type

    conf

  • DOI
    10.1109/ICDCS.1998.679491
  • Filename
    679491