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A reuse-oriented auxiliary construction method for software fault tree and tool implementation

机译:一种针对软件故障树和工具实现的重用导向的辅助施工方法

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Current SFTA methods highly rely on the experience of analysts and it's difficult to reuse history information of SFTA for current methods. With the increase of software complexity, the scale of software fault tree has increased explosively. Thus, there is an urgent need to effectively reuse history information of SFTA in order to avoid repeating analysis and improve efficiency. To organize fault tree information effectively, mine valuable patterns from history information and reuse SFTA information, this paper proposed a reuse-oriented auxiliary construction method for software fault tree. Firstly, a semi-formal method is proposed to define software fault tree information, which includes elements such as node, relation, type, target function and target software module. Then a knowledge base for software fault tree information is constructed. History information is indexed and reconstructed from several different attribute dimensions. Finally, by text matching and intelligent linking, a reusable sub fault tree is generated automatically from the knowledge base and can be inserted into another fault tree, achieving the goal of reusing SFTA information. The method proposed in this paper can effectively provide aid for SFTA, improve analysis efficiency and increase automation degree. Meanwhile, a tool based on this method is introduced in the paper, which also includes some other useful features such as automatic alignment of nodes, rule checking, minimal cut set calculation, qualitative analysis, and report generation. An example is provided in the paper to demonstrate how to use this method and validate the applicability, validity and efficiency of this method.
机译:目前的SFTA方法高度依赖于分析师的经验,并且难以重用SFTA的历史信息,以了解当前的方法。随着软件复杂性的增加,软件故障树的规模爆炸性地增加了。因此,迫切需要有效地重复使用SFTA的历史信息,以避免重复分析并提高效率。为了有效地组织故障树信息,挖掘历史信息和重用SFTA信息的宝贵模式,提出了一种用于软件故障树的重生辅助施工方法。首先,提出了一种半形式方法来定义软件故障树信息,包括节点,关系,类型,目标函数和目标软件模块等元素。然后构建软件故障树信息的知识库。历史信息从几个不同的属性维度索引并重建。最后,通过文本匹配和智能链接,可重用的子故障树从知识库自动生成,可以插入另一个故障树,实现重用SFTA信息的目标。本文提出的方法可以有效地为SFTA提供辅助,提高分析效率并提高自动化程度。同时,本文介绍了一种基于该方法的工具,其中还包括一些其他有用的特征,例如节点的自动对准,规则检查,最小剪切计算,定性分析和报告生成。本文提供了一个示例,以演示如何使用此方法并验证该方法的适用性,有效性和效率。

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