CPS设计与验证的主要数据流mocc综述

Guillaume Roumage, S. Azaiez, Stéphane Louise
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引用次数: 0

摘要

最近,汽车行业出于经济和生态方面的考虑,一直强调减少车内电子控制单元(ecu)的数量。这种减少意味着设计和验证必须独立于车辆的最终选择(MC) soc,因为知道它们会随着时间的推移而发展。为此,计算和通信的数据流模型(mocc)是维护这种独立性的强大工具。数据流mocc的一个子类——确定性数据流mocc——特别令人感兴趣,因为它允许设计人员在编译时派生安全性和安全性属性。本文对现有的确定性数据流mocc进行了简要的综述。我们描述了每个数据流MoCC的属性,并提出了一个数据流MoCC的表达层次结构,可根据设计人员的需要进行调整。
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A survey of main dataflow MoCCs for CPS design and verification
The automotive industry has recently emphasized reducing the number of Electronic Control Units (ECUs) installed in vehicles for economic and ecological reasons. This reduction means that the design and verification must be independent of the vehicle's final choice of (MC)SoCs, knowing they will evolve as time passes. To that end, dataflow Models of Computation and Communication (MoCCs) are powerful tools for maintaining this independence. A subclass of dataflow MoCCs -deterministic dataflow MoCCs- is of particular interest since it allows designers to derive safety and security properties at compile-time. This work proposes a short survey of the existing deterministic dataflow MoCCs. We describe the properties of each dataflow MoCC and present an expressiveness hierarchy of dataflow MoCCs adjustable to designers' needs.
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