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A Method for Merging Experts' Cause-Effect Knowledge in Software Dependability

机译:一种软件可靠性中因果关系知识的融合方法

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Software dependability engineering is an interdisciplinary area built on numerous concepts with complex interrelations. Understanding the relations between various concepts and integrating such conceptual knowledge is fundamental for educational, research and industrial purposes. This paper proposes a method to merge experts' conceptual knowledge represented in the form of Causal Mechanism Graphs (CMG). A case study was conducted to apply the method on 14 causal mechanism graphs obtained from 11 domain experts. The obtained consensus knowledge was then validated and evolved based on another 24 experts' opinions. The results demonstrate the main causal mechanisms that influence software dependability attributes, i.e. software aspect of reliability, safety, security, availability and maintainability. The application shows that the CMG merging method has the advantage of explicitly aggregating complex causal knowledge without losing information on the original knowledge structure. The application also shows that the CMG merging method is capable to integrate various factors that influence multiple dependability attributes at different stages of the software development lifecycle.
机译:软件可靠性工程是一个跨学科领域,它建立在具有复杂关系的众多概念上。理解各种概念之间的关系并整合这些概念性知识对于教育,研究和工业目的至关重要。本文提出了一种以因果图(CMG)形式表示的专家概念知识的合并方法。进行了案例研究,将该方法应用于从11位领域专家处获得的14个因果关系图上。然后,根据另外24位专家的意见对获得的共识知识进行验证和发展。结果证明了影响软件可靠性属性的主要因果机制,即可靠性,安全性,安全性,可用性和可维护性的软件方面。该应用程序显示,CMG合并方法的优点是可以显式聚合复杂的因果知识,而不会丢失原始知识结构上的信息。该应用程序还表明,CMG合并方法能够集成在软件开发生命周期的不同阶段影响多种可靠性属性的各种因素。

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