用于自治系统随机误差传播分析的UML/SysML行为图的自动转换

A. Morozov, Thomas Mutzke, K. Ding
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引用次数: 1

摘要

现代技术系统由异构部件组成,包括机械部件、硬件以及允许系统自主运行的广泛的软件部分。异构性和自主性需要适当的模型来描述组件之间的相互作用。UML和SysML是在早期设计阶段广泛接受的系统建模和基于模型的分析的候选工具,包括可靠性属性的分析。UML和SysML模型是半形式化的。因此,需要形式化模型的转换方法。最近,我们引入了一种随机双图误差传播模型(DEPM)。该模型捕获系统的控制和数据流结构,并允许使用概率模型检查技术计算高级风险度量。本文提出了一种新的自动转换方法,将带注释的状态机图与活动图扩展到分层的DEPM。这种方法将有助于可靠性工程师保持错误传播模型的更新,并确保其与可用的系统模型的一致性。详细描述了转换算法的功能和局限性,并在一个完整的基于模型的自主医疗患者表的错误传播分析中进行了演示。
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Automated Transformation of UML/SysML Behavioral Diagrams for Stochastic Error Propagation Analysis of Autonomous Systems
Modern technical systems consist of heterogeneous components, including mechanical parts, hardware, and the extensive software part that allows the autonomous system operation. The heterogeneity and autonomy require appropriate models that can describe the mutual interaction of the components. UML and SysML are widely accepted candidates for system modeling and model-based analysis in early design phases, including the analysis of reliability properties. UML and SysML models are semi-formal. Thus, transformation methods to formal models are required. Recently, we introduced a stochastic Dual-graph Error Propagation Model (DEPM). This model captures control and data flow structures of a system and allows the computation of advanced risk metrics using probabilistic model checking techniques. This article presents a new automated transformation method of an annotated State Machine Diagram, extended with Activity Diagrams, to a hierarchical DEPM. This method will help reliability engineers to keep error propagation models up to date and ensure their consistency with the available system models. The capabilities and limitations of transformation algorithm is described in detail and demonstrated on a complete model-based error propagation analysis of an autonomous medical patient table.
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来源期刊
CiteScore
5.20
自引率
13.60%
发文量
34
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