Remarks on Testing Probabilistic Processes
 
   Yuxin Deng, Rob van Glabbeek, Matthew Hennessy, Carroll Morgan, and Chenyi Zhang

We develop a general testing scenario for probabilistic processes, 
giving rise to two theories: \emph{probabilistic may testing} and 
\emph{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many of the axioms of standard testing  are no longer valid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 \emph{simulation}.
Using this, we obtain a complete axiomatisation for non-probabilistic
processes subject to probabilistic may testing.