Using Tools to Assist Identification of Non-requirements in Requirements Specifications - A Controlled Experiment

Using Tools to Assist Identification of Non-requirements in Requirements Specifications - A Controlled Experiment
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使用工具协助识别需求规范中的非需求 - 受控实验

DOI:
10.1007/978-3-319-77243-1_4
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发表时间:
2018
期刊:
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影响因子:
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通讯作者:
Andreas Vogelsang
Andreas Vogelsang
中科院分区:
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文献类型:
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作者:
J. Winkler;Andreas Vogelsang

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[背景和动机]在许多公司中,规范文档中的文本片段被分为需求和非需求。这种分类对于确定责任、导出测试用例以及更多决策非常重要。在实践中,这种分类通常是手动执行的,这使得其劳动密集型且容易出错。[问题/问题]我们开发了一种工具来帮助用户完成此任务,通过使用神经网络提供基于分类的警告。然而,我们目前不知道与不使用该工具相比,使用该工具是否真的有助于提高分类质量。[主要思想/结果]因此,我们对两组学生进行了对照实验。一组使用该工具来完成特定任务,而另一组则没有。通过比较两组的表现,我们可以评估我们的工具在哪些场景中的应用是有益的。[贡献]结果表明,只要准确性足够高,自动分类方法的应用可能会带来好处。
[Context and motivation]In many companies, textual fragments in specification documents are categorized into requirements and non-requirements. This categorization is important for determining liability, deriving test cases, and many more decisions. In practice, this categorization is usually performed manually, which makes it labor-intensive and error-prone.[Question/problem]We have developed a tool to assist users in this task by providing warnings based on classification using neural networks. However, we currently do not know whether using the tool actually helps increasing the classification quality compared to not using the tool.[Principal idea/results]Therefore, we performed a controlled experiment with two groups of students. One group used the tool for a given task, whereas the other did not. By comparing the performance of both groups, we can assess in which scenarios the application of our tool is beneficial.[Contribution]The results show that the application of an automated classification approach may provide benefits, given that the accuracy is high enough.