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
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;
Conference_Titel :
Distributed Computing Systems, 1998. Proceedings. 18th International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
0-8186-8292-2
DOI :
10.1109/ICDCS.1998.679491