安全关键软件及其异常的本体论分析

Hezhen Liu, Zhi Jin, Zheng Zheng, Chengqiang Huang, Xun Zhang
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引用次数: 0

摘要

软件在安全关键系统中逐渐占据主导地位,这引起了人们对软件可靠性的关注。评估软件可靠性和分析由软件异常触发的系统级危害的成熟实践和指南是有限的。一个问题是,尽管具有不同的性质,但表示软件异常的故障、错误和失败通常被模糊地用于预测软件的可靠性,从而导致不可靠的结果。这种共识概念化的缺乏还会导致支持工具之间的互操作性差,从而导致异常管理和软件维护方面的困难。由于异常的复杂性和安全关键性,异常分析和管理对于安全关键型软件来说更加困难。安全关键型软件的复杂环境导致在确定软件异常的演化/传播路径以及对系统安全的影响方面存在困难。为了捕捉安全关键型软件的本质并支持对软件异常和相关危害机制的理解,我们提出了三个参考本体:安全关键型软件本体、软件故障本体和软件故障诱导危害本体,它们是基于国际标准、指南和相关概念模型构建的。我们还讨论了它们之间的关系。这将有助于更好地理解软件异常机制和设计干预/缓解解决方案。我们将演示这些本体如何帮助分析现实世界安全关键系统的软件问题。
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An Ontological Analysis of Safety-Critical Software and Its Anomalies
The progressively dominant role of software in safety-critical systems raise concerns about the software dependability. There are limited mature practices and guides for assessing software dependability and analyzing system-level hazards triggered by software anomalies. A problem is that faults, errors, and failures that represent software anomalies, albeit with different natures, are usually used indistinctly to predict software dependability, leading to unsolid results. The lack of such consensual conceptualization also leads to poor interoperability between supporting tools, and, consequently, difficulties in anomaly management and software maintenance. Anomaly analysis and management is more tough for safety-critical software due to its higher complexity and the safety-critical nature. The complex context of safety-critical software causes difficulties in determining the evolution/propagation path of software anomalies and the impact on system safety. To capture the nature of safety-critical software and support an understanding of mechanisms of software anomalies and associated hazards, we propose three reference ontologies: Safety-critical Software Ontology, Software Fault Ontology and Software-failure-induced Hazard Ontology, which are built based on international standards, guides, and relevant conceptual models. We also discuss the relationships among them. That will facilitate a better understanding of the software anomaly mechanisms and the design of intervening/mitigation solutions. We demonstrate how these ontologies can help analyze software problems of real-world safety-critical systems.
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