A unifying approach to probabilistic testing equivalences.

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Title: A unifying approach to probabilistic testing equivalences.
Authors: Chen, Weijun1 (AUTHOR) cwj2018@sjtu.edu.cn, Fu, Yuxi1 (AUTHOR) fu-yx@cs.sjtu.edu.cn, Long, Huan1 (AUTHOR) longhuan@sjtu.edu.cn, Wu, Hao2 (AUTHOR) wuhao@shmtu.edu.cn
Source: Theoretical Computer Science. Jun2026, Vol. 1075, pN.PAG-N.PAG. 1p.
Subjects: Semantics methodology, Predicate calculus, Stochastic processes
Abstract: Probabilistic concurrent systems are foundational models for modern mobile computing. In this paper, a unifying approach to probabilistic testing equivalences 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 internal 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 congruences. 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. To showcase this flexibility, a case study is carried out on the pCSP model. [ABSTRACT FROM AUTHOR]
Copyright of Theoretical Computer Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Probabilistic concurrent systems are foundational models for modern mobile computing. In this paper, a unifying approach to probabilistic testing equivalences 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 internal 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 congruences. 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. To showcase this flexibility, a case study is carried out on the pCSP model. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Theoretical Computer Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.tcs.2026.115928
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      – Code: eng
        Text: English
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      – SubjectFull: Predicate calculus
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      – SubjectFull: Stochastic processes
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      – TitleFull: A unifying approach to probabilistic testing equivalences.
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              Text: Jun2026
              Type: published
              Y: 2026
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