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Techniques and applications of computation slicing

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Abstract.

Writing correct distributed programs is hard. In spite of extensive testing and debugging, software faults persist even in commercial grade software. Many distributed systems should be able to operate properly even in the presence of software faults. Monitoring the execution of a distributed system, and, on detecting a fault, initiating the appropriate corrective action is an important way to tolerate such faults. This gives rise to the predicate detection problem which requires finding whether there exists a consistent cut of a given computation that satisfies a given global predicate.

Detecting a predicate in a computation is, however, an NP-complete problem in general. In order to ameliorate the associated combinatorial explosion problem, we introduce the notion of computation slice. Formally, the slice of a computation with respect to a predicate is a (sub)computation with the least number of consistent cuts that contains all consistent cuts of the computation satisfying the predicate. Intuitively, slice is a concise representation of those consistent cuts of a computation that satisfy a certain condition. To detect a predicate, rather than searching the state-space of the computation, it is much more efficient to search the state-space of the slice.

We prove that the slice of a computation is uniquely defined for all predicates. We also present efficient algorithms for computing the slice for several useful classes of predicates. For an arbitrary predicate, we establish that the problem of computing the slice is NP-complete in general. Nonetheless, for such a predicate, we develop an efficient heuristic algorithm for computing an approximate slice. Our experimental results demonstrate that slicing can lead to an exponential improvement over existing techniques for predicate detection in terms of time and space.

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Authors and Affiliations

  1. Department of Computer Science, The University of Texas at Dallas, TX 75083, Richardson, USA

    Neeraj Mittal

  2. Department of Electrical and Computer Engineering, The University of Texas at Austin, TX 78712, Austin, USA

    Vijay K. Garg

Authors
  1. Neeraj Mittal
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  2. Vijay K. Garg
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Corresponding author

Correspondence to Neeraj Mittal.

Additional information

Received: 19 November 2003, Revised: 29 July 2004, Published online: 7 February 2005

Vijay K. Garg: Supported in part by the NSF Grants ECS-9907213, CCR-9988225, Texas Education Board Grant ARP-320, an Engineering Foundation Fellowship, and an IBM grant.

Parts of this paper have appeared earlier in conference proceedings [GM01,MG01a,MG03a].

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Mittal, N., Garg, V.K. Techniques and applications of computation slicing. Distrib. Comput. 17, 251–277 (2005). https://doi.org/10.1007/s00446-004-0117-0

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