An Empirical Study on the Risks of Using Off-the-Shelf Techniques for Processing Mailing List Data

被引:20
|
作者
Bettenburg, Nicolas [1 ]
Shihab, Emad [1 ]
Hassan, Ahmed E. [1 ]
机构
[1] Queens Univ, Software Anal & Intelligence Lab, Kingston, ON, Canada
关键词
D O I
10.1109/ICSM.2009.5306383
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Mailing list repositories contain valuable information about the history of a project. Research is starting to mine this information to support developers and maintainers of long-lived software projects. However, such information exists as unstructured data that needs special processing before it can be studied. In this paper, we identify several challenges that arise when using off-the-shelf techniques for processing mailing list data. Our study highlights the importance of proper processing of mailing list data to ensure accurate research results.
引用
收藏
页码:539 / 542
页数:4
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