A Model-Independent Theory of Probabilistic Testing
By: Weijun Chen , Yuxi Fu , Huan Long and more
Potential Business Impact:
Tests computer programs that make many choices.
Probabilistic concurrent systems are foundational models for modern mobile computing. In this paper, a general model-independent approach to probabilistic testing is proposed. With the help of a new distribution-based semantics for probabilistic models and a probabilistic testing framework with respect to process predicates, the model-independent characterization and the external characterization for testing equivalences are studied. The latter characterization can be viewed as the generalization of the classical fair/should equivalence and may equivalence. These equivalences are shown to be congruent. A thorough comparison between these equivalences and probabilistic bisimilarities is carried out. The techniques introduced in this paper can be easily extended to other probabilistic concurrent models.
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