Real Reward Testing for Probabilistic Processes
Citation:
Yuxin Deng, Rob vanGlabbeek, Matthew Hennessy and Carroll Morgan, Real Reward Testing for Probabilistic Processes, Ninth Workshop on Quantitative Aspects of Programming Languages (QAPL 2011), Saarbrucken, Germany, April, 2011Download Item:
Abstract:
We introduce a notion of real reward testing for probabilistic processes
by extending the traditional nonnegative reward testing with negative rewards.
In this testing framework, the may and must preorders turn out to be the inverse
relations of each other. We show that for convergent processes with finitely
many states and transitions, but not in the presence of divergence, the real reward
must testing preorder coincides with the nonnegative reward must testing
preorder. To prove this coincidence we characterise the usual resolution based
testing in terms of the weak transitions of processes, without involving policies,
adversaries, schedulers, resolutions, or similar structures that are external to the
process under investigation. This requires establishing the continuity of our function
for calculating testing outcomes.
Author's Homepage:
http://people.tcd.ie/mcbhenneDescription:
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Author: HENNESSY, MATTHEW
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Full text availableKeywords:
Computer sciences, real reward testingMetadata
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