Quantitative Model Checking of Linear-Time Properties Based on Generalized Possibility Measures
Yongming Li

TL;DR
This paper develops a quantitative model checking framework for fuzzy linear-time properties using generalized possibility measures, extending previous qualitative approaches to incorporate uncertainty in system models and properties.
Contribution
It introduces generalized possibilistic Kripke structures and studies verification of fuzzy linear-time properties, including safety and liveness, using fuzzy automata.
Findings
Verification reduces to reachability and persistence checks in product structures.
Fuzzy regular safety and ω-regular properties can be verified using fuzzy automata.
The methods are illustrated with concrete examples.
Abstract
Model checking of linear-time properties based on possibility measures was studied in previous work (Y. Li and L. Li, Model checking of linear-time properties based on possibility measure, IEEE Transactions on Fuzzy Systems, 21(5)(2013), 842-854). However, the linear-time properties considered in the previous work was classical and qualitative, possibility information of the systems was not considered at all. We shall study quantitative model checking of fuzzy linear-time properties based on generalized possibility measures in the paper. Both the model of the system, as well as the properties the system needs to adhere to, are described using possibility information to identify the uncertainty in the model/properties. The systems are modeled by {\sl generalized possibilistic Kripke structures} (GPKS, in short), and the properties are described by fuzzy linear-time properties.…
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Taxonomy
TopicsFormal Methods in Verification · Software Reliability and Analysis Research · Risk and Safety Analysis
