TransDPOR: a novel dynamic partial-order reduction technique for testing actor programs

  • Authors:

  • Samira Tasharofi;Rajesh K. Karmani;Steven Lauterburg;Axel Legay;Darko Marinov;Gul Agha

  • Affiliations:

  • Department of Computer Science, University of Illinois, Urbana, IL;Department of Computer Science, University of Illinois, Urbana, IL;Salisbury University, Salisbury, MD;INRIA, France;Department of Computer Science, University of Illinois, Urbana, IL;Department of Computer Science, University of Illinois, Urbana, IL

  • Venue:
  • FMOODS'12/FORTE'12 Proceedings of the 14th joint IFIP WG 6.1 international conference and Proceedings of the 32nd IFIP WG 6.1 international conference on Formal Techniques for Distributed Systems
  • Year:
  • 2012

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Abstract

To detect hard-to-find concurrency bugs, testing tools try to systematically explore all possible interleavings of the transitions in a concurrent program. Unfortunately, because of the nondeterminism in concurrent programs, exhaustively exploring all interleavings is time-consuming and often computationally intractable. Speeding up such tools requires pruning the state space explored. Partial-order reduction (POR) techniques can substantially prune the number of explored interleavings. These techniques require defining a dependencyrelation on transitions in the program, and exploit independency among certain transitions to prune the state space. We observe that actor systems, a prevalent class of programs where computation entities communicate by exchanging messages, exhibit a dependency relation among co-enabled transitions with an interesting property: transitivity. This paper introduces a novel dynamic POR technique, TransDPOR, that exploits the transitivity of the dependency relation in actor systems. Empirical results show that leveraging transitivity speeds up exploration by up to two orders of magnitude compared to existing POR techniques.