This paper presents an approach for modeling software common cause failures (CCFs) within digital instrumentation and control (I&C) systems. CCFs consist of a concurrent failure between two or more components due to a shared failure cause and coupling mechanism. This work emphasizes the importance of identifying software-centric attributes related to the coupling mechanisms necessary for simultaneous failures of redundant software components. The groups of components that share coupling mechanisms are called common cause component groups (CCCGs). Most CCF models rely on operational data as the basis for establishing CCCG parameters and predicting CCFs. This work is motivated by two primary concerns: (1) a lack of operational and CCF data for estimating software CCF model parameters; and (2) the need to model single components as part of multiple CCCGs simultaneously. A hybrid approach was developed to account for these concerns by leveraging existing techniques: a modified beta factor model allows single components to be placed within multiple CCCGs, while a second technique provides software-specific model parameters for each CCCG. This hybrid approach provides a means to overcome the limitations of conventional methods while offering support for design decisions under the limited data scenario.

翻译：本文件介绍了在数字仪表和控制(I&C)系统内模拟软件常见原因失灵(CCF)的一种方法。CCF包括两个或两个以上组成部分由于共同失败原因和合并机制而同时发生的故障。这项工作强调,必须确定与多余软件组件同时失灵所必要的混合机制有关的以软件为中心的特性。共享组合机制的部件组称为共同原因组成组(CCCGs)。大多数CCCF模型都以业务数据作为建立CCCG参数和预测CCF的基础。这项工作有两个主要关切的动机:(1) 缺乏用于估计软件CCF模型参数的操作数据和CCF数据;(2) 需要同时将单个组成部分作为多个CCCG的一部分来建模。制定了一种混合方法,通过利用现有技术来考虑这些关切:一个修改后的Bita因子模型允许将单个组成部分置于多个CCCG内,而第二个技术为每个CCCG提供了软件特定的模型参数。这种混合方法提供了克服传统方法局限性的手段,同时在有限的数据设想下为设计决定提供支持。