An Empirical Study on Source Code Feature Extraction in Preprocessing of IR-Based Requirements Traceability

Bangchao Wang, Yang Deng, Ruiqi Luo, Huan Jin
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引用次数: 1

Abstract

In information retrieval-based (IR-based) requirements traceability research, a great deal of researches have focused on establishing trace links between requirements and source code. However, as the description styles of source code and requirements are very different, how to better preprocess the code is crucial for the quality of trace link generation. This paper aims to draw empirical conclusions about code feature extraction, annotation importance assessment, and annotation redundancy removal through comprehensive experiments, which impact the quality of trace links generated by IR-based methods between requirements and source code. The results show that when the average annotaion density is higher than 0.2, feature extraction is recommended. Removing redundancy from code with high annotation redundancy can enhance the quality of trace links. The above experiences can help developers to improve the quality of trace link generation and provide them with advice on writing code.
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基于ir的需求追溯预处理中源代码特征提取的实证研究
在基于信息检索(ir)的需求可追溯性研究中,大量的研究集中在建立需求和源代码之间的跟踪链接。然而,由于源代码和需求的描述风格有很大的不同,如何更好地对代码进行预处理对跟踪链接生成的质量至关重要。本文旨在通过综合实验得出影响需求与源代码之间基于ir方法生成的跟踪链接质量的代码特征提取、标注重要性评估和标注冗余去除的经验结论。结果表明,当平均标注密度大于0.2时,建议进行特征提取。从注释冗余度高的代码中去除冗余可以提高跟踪链接的质量。以上经验可以帮助开发人员提高跟踪链接生成的质量,并为他们编写代码提供建议。
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