Improving Verification Accuracy of CPS by Modeling and Calibrating Interaction Uncertainty

Author:

Yang Wenhua1,Xu Chang1,Pan Minxue2,Ma Xiaoxing1,Lu Jian1

Affiliation:

1. State Key Laboratory for Novel Software Technology and Department of Computer Science and Technology, Nanjing University, P.R. China

2. State Key Laboratory for Novel Software Technology and Software Institute, Nanjing University, P.R. China

Abstract

Cyber-Physical Systems (CPS) intrinsically combine hardware and physical systems with software and network, which are together creating complex and correlated interactions. CPS applications often experience uncertainty in interacting with environment through unreliable sensors. They can be faulty and exhibit runtime errors if developers have not considered environmental interaction uncertainty adequately. Existing work in verifying CPS applications ignores interaction uncertainty and thus may overlook uncertainty-related faults. To improve verification accuracy, in this article we propose a novel approach to verifying CPS applications with explicit modeling of uncertainty arisen in the interaction between them and the environment. Our approach builds an Interactive State Machine network for a CPS application and models interaction uncertainty by error ranges and distributions. Then it encodes both the application and uncertainty models to Satisfiability Modulo Theories (SMT) formula to leverage SMT solvers searching for counterexamples that represent application failures. The precision of uncertainty model can affect the verification results. However, it may be difficult to model interaction uncertainty precisely enough at the beginning, because of the uncontrollable noise of sensors and insufficient data sample size. To further improve the accuracy of the verification results, we propose an approach to identifying and calibrating imprecise uncertainty models. We exploit the inconsistency between the counterexamples’ estimate and actual occurrence probabilities to identify possible imprecision in uncertainty models, and the calibration of imprecise models is to minimize the inconsistency, which is reduced to a Search-Based Software Engineering problem. We experimentally evaluated our verification and calibration approaches with real-world CPS applications, and the experimental results confirmed their effectiveness and efficiency.

Funder

National Key R8D Program of China

National Natural Science Foundation

Natural Science Foundation of Jiangsu Province

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ensure: Towards Reliable Control of Cyber-Physical Systems Under Uncertainty;IEEE Transactions on Reliability;2023-03

2. An interactive fault detection method for cyber-physical system based on system-theoretic process analysis;2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022);2022-04-25

3. Uncertainty handling in cyber–physical systems: State‐of‐the‐art approaches, tools, causes, and future directions;Journal of Software: Evolution and Process;2022-01-20

4. Seamless validation of cyber-physical systems under real-time conditions by using a cyber-physical laboratory test field;2021 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE);2021-12-12

5. Generic Adaptive Scheduling for Efficient Context Inconsistency Detection;IEEE Transactions on Software Engineering;2021-03-01

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