Simulink is widely used for model-driven development (MDD) of cyber-physical systems. Typically, the Simulink-based development starts with Stateflow modeling, followed by simulation, validation, and code generation mapped to physical execution platforms. However, recent trends have raised the demands of rigorous verification on safety-critical applications to prevent intrinsic development faults and improve the system dependability, which is unfortunately challenging. Even though the constructed Stateflow model and the generated code pass the validation of Simulink Design Verifier and Simulink Polyspace, respectively, the system may still fail due to some implicit defects contained in the design model (design defect) and the generated code (implementation defects).In this article, we bridge the Stateflow-based MDD and a well-defined rigorous verification to reduce development faults. First, we develop a self-contained toolkit to translate a Stateflow model into timed automata, where major advanced modeling features in Stateflow are supported. Taking advantage of the strong verification capability of Uppaal, we can not only find bugs in Stateflow models that are missed by Simulink Design Verifier but also check more important temporal properties. Next, we customize a runtime verifier for the generated non-intrusive VHDL and C code of a Stateflow model for monitoring. The major strength of the customization is the flexibility to collect and analyze runtime properties with a pure software monitor, which offers more opportunities for engineers to achieve high reliability of the target system compared with the traditional act that only relies on Simulink Polyspace. In this way, safety-critical properties are both verified at the model level and at the consistent system implementation level with physical execution environment in consideration. We apply our approach to the development of a typical cyber-physical system-train communication controller based on the IEC standard 61375. Experiments show that more ambiguousness in the standard are detected and confirmed and more development faults and those corresponding errors that would lead to system failure have been removed. Furthermore, the verified implementation has been deployed on real trains.
CITATION STYLE
Jiang, Y., Song, H., Yang, Y., Liu, H., Gu, M., Guan, Y., … Sha, L. (2019). Dependable Model-driven Development of CPS. ACM Transactions on Cyber-Physical Systems, 3(1), 1–31. https://doi.org/10.1145/3078623
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