SeSaMe: A Data Set of Semantically Similar Java Methods

Marius Kamp, Patrick Kreutzer, M. Philippsen
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引用次数: 5

Abstract

In the past, techniques for detecting similarly behaving code fragments were often only evaluated with small, artificial oracles or with code originating from programming competitions. Such code fragments differ largely from production codes. To enable more realistic evaluations, this paper presents SeSaMe, a data set of method pairs that are classified according to their semantic similarity. We applied text similarity measures on JavaDoc comments mined from 11 open source repositories and manually classified a selection of 857 pairs.
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SeSaMe:语义相似的Java方法的数据集
在过去,检测行为相似的代码片段的技术通常只使用小型的人工预言机或来自编程竞赛的代码进行评估。这样的代码片段与产品代码有很大的不同。为了实现更真实的评估,本文提出了SeSaMe,这是一个根据语义相似度进行分类的方法对数据集。我们对从11个开源存储库中挖掘的JavaDoc注释应用了文本相似性度量,并手动分类了857对。
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