Mining the coherence of GNOME bug reports with statistical topic models

Erik J. Linstead, P. Baldi
{"title":"Mining the coherence of GNOME bug reports with statistical topic models","authors":"Erik J. Linstead, P. Baldi","doi":"10.1109/MSR.2009.5069486","DOIUrl":null,"url":null,"abstract":"We adapt Latent Dirichlet Allocation to the problem of mining bug reports in order to define a new information-theoretic measure of coherence. We then apply our technique to a snapshot of the GNOME Bugzilla database consisting of 431,863 bug reports for multiple software projects. In addition to providing an unsupervised means for modeling report content, our results indicate substantial promise in applying statistical text mining algorithms for estimating bug report quality. Complete results are available from our supplementary materials website at http://sourcerer.ics.uci.edu/msr2009/gnome_coherence.html.","PeriodicalId":413721,"journal":{"name":"2009 6th IEEE International Working Conference on Mining Software Repositories","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 6th IEEE International Working Conference on Mining Software Repositories","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSR.2009.5069486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40

Abstract

We adapt Latent Dirichlet Allocation to the problem of mining bug reports in order to define a new information-theoretic measure of coherence. We then apply our technique to a snapshot of the GNOME Bugzilla database consisting of 431,863 bug reports for multiple software projects. In addition to providing an unsupervised means for modeling report content, our results indicate substantial promise in applying statistical text mining algorithms for estimating bug report quality. Complete results are available from our supplementary materials website at http://sourcerer.ics.uci.edu/msr2009/gnome_coherence.html.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用统计主题模型挖掘GNOME bug报告的一致性
我们将潜在狄利克雷分配方法应用到bug报告挖掘问题中,以定义一种新的相干性的信息论度量。然后将我们的技术应用于GNOME Bugzilla数据库的快照,该数据库包含多个软件项目的431,863个bug报告。除了提供一种无监督的方法来对报告内容进行建模之外,我们的结果表明在应用统计文本挖掘算法来估计bug报告质量方面有很大的前景。完整的结果可从我们的补充材料网站http://sourcerer.ics.uci.edu/msr2009/gnome_coherence.html获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Tracking concept drift of software projects using defect prediction quality Mining the history of synchronous changes to refine code ownership Learning from defect removals Assigning bug reports using a vocabulary-based expertise model of developers Using association rules to study the co-evolution of production & test code
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1