Abstract
Reliability is a fundamental property for mission and safety-critical systems, and adopting redundancy architectures is a common and prominent practice to increase system reliability. This paper proposes a novel approach for the modeling and quantitative reliability analysis of redundancy architectures based on the SBIP framework. Our approach supports modeling the nominal system behavior and the system faults in a unified formal model, which can be further integrated into the rigorous component-based system design paradigm advocated by BIP. We also propose two categories of metrics for formal reliability evaluation of redundancy architectures in terms of whether the system can operate correctly or provide reduced functionalities in the presence of faults. We take a computation unit as the running example and apply the proposed approach to analyze static redundancy and dynamic redundancy, which are Triple Module Redundancy architecture and Cold Standby architecture respectively. The experimental results show that our approach can accurately model various redundancy architectures and provide a comprehensive analysis of reliability and related properties in an automated manner. Moreover, our approach can be easily extended to a wide range of fault types and behaviors.
H. He and H. Kuang—Contribute equally to this work.
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Acknowledgment
This work was supported by National Natural Science Foundation of China (Grant No. 62106150).
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He, H., Kuang, H., Yang, L., Yang, F., Wang, Q., Cao, W. (2022). Automated Reliability Analysis of Redundancy Architectures Using Statistical Model Checking. In: Memmi, G., Yang, B., Kong, L., Zhang, T., Qiu, M. (eds) Knowledge Science, Engineering and Management. KSEM 2022. Lecture Notes in Computer Science(), vol 13370. Springer, Cham. https://doi.org/10.1007/978-3-031-10989-8_37
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