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Means-ends and whole-part traceability analysis of safety requirements

机译:安全要求的均值和全部分可追溯性分析

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Safety is a system property, hence the high-level safety requirements are incorporated into the implementation of system components. In this paper, we propose an optimized traceability analysis method which is based on the means-ends and whole-part concept of the approach for cognitive systems engineering to trace these safety requirements. A system consists of hardware, software, and humans according to a whole-part decomposition. The safety requirements of a system and its components are enforced or implemented through a means-ends lifecycle. To provide evidence of the safety of a system, the means-ends and whole-part traceability analysis method will optimize the creation of safety evidence from the safety requirements, safety analysis results, and other system artifacts produced through a life-cycle. These sources of safety evidence have a causal (cause-consequence) relationship between each other. The failure mode and effect analysis (FMEA), the hazard and operability analysis (HAZOP), and the fault tree analysis (FTA) techniques are generally used for safety analysis of systems and their components. These techniques cover the causal relations in a safety analysis. The causal relationships in the proposed method make it possible to trace the safety requirements through the safety analysis results and system artifacts. We present the proposed approach with an example, and described the usage of TRACE and NuSRS tools to apply the approach.
机译:安全是系统的属性,因此高级别的安全要求已纳入系统组件的实现中。在本文中,我们提出了一种优化的可追溯性分析方法,该方法基于认知系统工程方法的均方根和整体概念来跟踪这些安全要求。根据整个部分的分解,系统由硬件,软件和人员组成。系统和组件的安全要求是通过手段端生命周期强制执行或实施的。为了提供系统安全性的证据,均值端和整个部分的可追溯性分析方法将从安全要求,安全性分析结果以及整个生命周期中产生的其他系统工件中优化安全性证据的创建。这些安全证据来源之间存在因果关系(因果关系)。故障模式和影响分析(FMEA),危害和可操作性分析(HAZOP)以及故障树分析(FTA)技术通常用于系统及其组件的安全性分析。这些技术涵盖了安全性分析中的因果关系。所提出的方法中的因果关系使得可以通过安全性分析结果和系统工件来跟踪安全性需求。我们通过一个示例介绍提出的方法,并描述了TRACE和NuSRS工具在该方法中的用法。

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