Abstract
Model checking is a formal automatic verification technology for complex concurrent systems. It is used widely in the verification and analysis of computer software and hardware systems, communication protocols, security protocols, etc. The generalized possibilistic μ-calculus model-checking algorithm for decision processes is studied to solve the formal verification problem of concurrent systems with nondeterministic information and incomplete information on the basis of possibility theory. Firstly, the generalized possibilistic decision process is introduced as the system model. Then, the classical proposition μ-calculus is improved and extended, and the concept of generalized possibilistic μ-calculus (GPoμ) is given to describe the attribute characteristics of nondeterministic systems. Then, the GPoμ model-checking algorithm is proposed, and the model-checking problem is simplified to fuzzy matrix operations. Finally, a specific example and a case study are analyzed and verified. Compared with the classical μ-calculus, the generalized possibilistic μ-calculus has a stronger expressive power and can better characterize the attributes of nondeterministic systems. The model-checking algorithm can give the possibility that the system satisfies the attributes. The research work provides a new idea and method for model checking nondeterministic systems.
Highlights
The continuous enhancement of computer functions makes systems increasingly complex; for the purpose of the correctness of the systems, it usually spends more time on verification than on construction [1]
The classical model-checking technology is mainly used for qualitative research on the system—that is, to verify if the system satisfies the system attributes described by temporal logic formulas, such as Computation Tree Logic (CTL), Linear Temporal Logic (LTL), and μ-calculus [3,4]
Li et al proposed Generalized Possibilistic LTL (GPoLTL), which is an extension of LTL, and gave quantitative model checking methods of linear-time properties based on generalized possibility measures in [18]
Summary
The continuous enhancement of computer functions makes systems increasingly complex; for the purpose of the correctness of the systems, it usually spends more time on verification than on construction [1]. Li et al proposed Generalized Possibilistic LTL (GPoLTL), which is an extension of LTL, and gave quantitative model checking methods of linear-time properties based on generalized possibility measures in [18]. They extended CTL to Generalized Possibilistic CTL (GPoCTL) and proposed a model-checking algorithm under the generalized possibilistic decision process in [21].
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