Remarks on Testing Probabilistic Processes

  • Authors:

  • Yuxin Deng;Rob van Glabbeek;Matthew Hennessy;Carroll Morgan;Chenyi Zhang

  • Affiliations:

  • School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia;National ICT Australia, Locked Bag 6016, Sydney, NSW 1466, Australia and School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia;Department of Informatics, University of Sussex, Falmer, Brighton, BN1 9QN, UK and National ICT Australia, Locked Bag 6016, Sydney, NSW 1466, Australia;School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia;National ICT Australia, Locked Bag 6016, Sydney, NSW 1466, Australia and School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia

  • Venue:
  • Electronic Notes in Theoretical Computer Science (ENTCS)
  • Year:
  • 2007

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Abstract

We develop a general testing scenario for probabilistic processes, giving rise to two theories: probabilistic may testing and probabilistic must testing. These are applied to a simple probabilistic version of the process calculus CSP. We examine the algebraic theory of probabilistic testing, and show that many of the axioms of standard testing are no longer valid in our probabilistic setting; even for non-probabilistic CSP processes, the distinguishing power of probabilistic tests is much greater than that of standard tests. We develop a method for deriving inequations valid in probabilistic may testing based on a probabilistic extension of the notion of simulation. Using this, we obtain a complete axiomatisation for non-probabilistic processes subject to probabilistic may testing.