Bugs.jar: A Large-Scale, Diverse Dataset of Real-World Java Bugs

Ripon K. Saha, Yingjun Lyu, Wing Lam, H. Yoshida, M. Prasad
{"title":"Bugs.jar: A Large-Scale, Diverse Dataset of Real-World Java Bugs","authors":"Ripon K. Saha, Yingjun Lyu, Wing Lam, H. Yoshida, M. Prasad","doi":"10.1145/3196398.3196473","DOIUrl":null,"url":null,"abstract":"We present Bugs.jar, a large-scale dataset for research in automated debugging, patching, and testing of Java programs. Bugs.jar is comprised of 1,158 bugs and patches, drawn from 8 large, popular opensource Java projects, spanning 8 diverse and prominent application categories. It is an order of magnitude larger than Defects4J, the only other dataset in its class. We discuss the methodology used for constructing Bugs.jar, the representation of the dataset, several use-cases, and an illustration of three of the use-cases through the application of 3 specific tools on Bugs.jar, namely our own tool, Elixir, and two third-party tools, Ekstazi and JaCoCo.","PeriodicalId":6639,"journal":{"name":"2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR)","volume":"1 1","pages":"10-13"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"144","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3196398.3196473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 144

Abstract

We present Bugs.jar, a large-scale dataset for research in automated debugging, patching, and testing of Java programs. Bugs.jar is comprised of 1,158 bugs and patches, drawn from 8 large, popular opensource Java projects, spanning 8 diverse and prominent application categories. It is an order of magnitude larger than Defects4J, the only other dataset in its class. We discuss the methodology used for constructing Bugs.jar, the representation of the dataset, several use-cases, and an illustration of three of the use-cases through the application of 3 specific tools on Bugs.jar, namely our own tool, Elixir, and two third-party tools, Ekstazi and JaCoCo.
bug .jar:一个大规模的、多样化的真实世界Java bug数据集
我们提供了Bugs.jar,这是一个大规模的数据集,用于研究Java程序的自动调试、修补和测试。jar由1158个bug和补丁组成,这些bug和补丁来自8个大型、流行的开源Java项目,涵盖8个不同且突出的应用程序类别。它比同类中唯一的另一个数据集Defects4J大一个数量级。我们讨论了构建Bugs.jar的方法、数据集的表示、几个用例,并通过在Bugs.jar上应用3个特定工具(即我们自己的工具Elixir和两个第三方工具Ekstazi和JaCoCo)来说明其中3个用例。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信