一种实用的DPRA模型维修性度量方法
A Pragmatic Approach for Measuring Maintainability of DPRA Models
摘要：
动态概率风险评估（DPRA）是一个强大的概念，用于评估复杂的工业系统的设计和安全。DPRA模型使用概念系统表示作为模拟和分析的正式基础。在本文中，我们考虑的自适应维护的DPRA模型，包括修改和扩展一个简化的模型，一个真正大小的DPRA模型。我们提出了一种定量的可维护性评估的DPRA模型创建的工业建模工具PyCATSHOO的方法。我们回顾并采用概念建模、软件工程和OO设计中的一些度量来评估PyCATSHOO模型的可维护性。在著名的“加热室”测试案例的例子中，我们说明了如何选择的指标可以作为模型的可修改性和复杂性的早期指标。这些指标将使专家能够在DPRA模型开发生存周期的早期做出更好的决策。
英文摘要：
Dynamic Probabilistic Risk Assessment (DPRA) is a powerful concept that is used to evaluate design and safety of complex industrial systems. A DPRA model uses a conceptual system representation as a formal basis for simulation and analysis. In this paper we consider an adaptive maintenance of DPRA models that consist in modifying and extending a simplified model to a real-size DPRA model. We propose an approach for quantitative maintainability assessment of DPRA models created with an industrial modeling tool called PyCATSHOO. We review and adopt some metrics from conceptual modeling, software engineering and OO design for assessing maintainability of PyCATSHOO models. On the example of well-known "Heated Room" test case, we illustrate how the selected metrics can serve as early indicators of model modifiability and complexity. These indicators would allow experts to make better decisions early in the DPRA model development life cycle.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
