从状态流仿真到验证实现:一种验证方法和实时列车控制器设计

Yu Jiang, Yixiao Yang, Han Liu, Hui Kong, M. Gu, Jiaguang Sun, L. Sha
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引用次数: 31

摘要

Simulink被广泛应用于工业软件系统的模型驱动开发(MDD)。通常,基于Simulink的开发是从状态流建模开始的,然后是模拟、验证和映射到物理执行平台的代码生成。然而,最近的工业趋势提高了对安全关键应用的严格验证的要求,不幸的是,这对Simulink来说是一个挑战。在本文中,我们提出了一种将基于状态流的模型驱动开发和定义良好的严格验证连接起来的方法。首先,我们开发了一个自包含的工具包来将Stateflow模型转换为时间自动机,其中支持Stateflow中的主要高级建模功能。利用Uppaal强大的验证能力,我们不仅可以发现Simulink Design Verifier没有发现的状态流模型中的错误,还可以检查更重要的时间属性。接下来,我们为生成的非侵入式VHDL和C代码定制一个运行时验证器,用于监控状态流模型。定制化的主要优势在于使用纯软件监视器灵活地收集和分析运行时属性,与仅依赖于Simulink Polyspace的传统行为相比,这为工程师实现目标系统的高可靠性提供了更多机会。我们将这两个部分无缝地合并到原始的基于状态流的MDD中。通过这种方式,在模型级别和考虑物理执行环境的一致系统实现级别都验证了安全关键属性。我们将该方法应用于列车控制器设计,并在实际硬件平台上进行了测试和部署。
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From Stateflow Simulation to Verified Implementation: A Verification Approach and A Real-Time Train Controller Design
Simulink is widely used for model driven development (MDD) of industrial software systems. Typically, the Simulink based development is initiated from Stateflow modeling, followed by simulation, validation and code generation mapped to physical execution platforms. However, recent industrial trends have raised the demands of rigorous verification on safety-critical applications, which is unfortunately challenging for Simulink. In this paper, we present an approach to bridge the Stateflow based model driven development and a well- defined rigorous verification. First, we develop a self- contained toolkit to translate 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 which are missed by Simulink Design Verifier, but also check more important temporal properties. Next, we customize a runtime verifier for the generated nonintrusive VHDL and C code of 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 opens more opportunities for engineers to achieve high reliability of the target system compared with the traditional act that only relies on Simulink Polyspace. We incorporate these two parts into original Stateflow based MDD seamlessly. 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 on a train controller design, and the verified implementation is tested and deployed on a real hardware platform.
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