JavaVFC:开源软件的 Java 漏洞修复承诺

Tan Bui, Yan Naing Tun, Yiran Cheng, Ivana Clairine Irsan, Ting Zhang, Hong Jin Kang
{"title":"JavaVFC:开源软件的 Java 漏洞修复承诺","authors":"Tan Bui, Yan Naing Tun, Yiran Cheng, Ivana Clairine Irsan, Ting Zhang, Hong Jin Kang","doi":"arxiv-2409.05576","DOIUrl":null,"url":null,"abstract":"We present a comprehensive dataset of Java vulnerability-fixing commits\n(VFCs) to advance research in Java vulnerability analysis. Our dataset, derived\nfrom thousands of open-source Java projects on GitHub, comprises two variants:\nJavaVFC and JavaVFC-extended. The dataset was constructed through a rigorous\nprocess involving heuristic rules and multiple rounds of manual labeling. We\ninitially used keywords to filter candidate VFCs based on commit messages, then\nrefined this keyword set through iterative manual labeling. The final labeling\nround achieved a precision score of 0.7 among three annotators. We applied the\nrefined keyword set to 34,321 open-source Java repositories with over 50 GitHub\nstars, resulting in JavaVFC with 784 manually verified VFCs and\nJavaVFC-extended with 16,837 automatically identified VFCs. Both variants are\npresented in a standardized JSONL format for easy access and analysis. This\ndataset supports various research endeavors, including VFC identification,\nfine-grained vulnerability detection, and automated vulnerability repair. The\nJavaVFC and JavaVFC-extended are publicly available at\nhttps://zenodo.org/records/13731781.","PeriodicalId":501278,"journal":{"name":"arXiv - CS - Software Engineering","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"JavaVFC: Java Vulnerability Fixing Commits from Open-source Software\",\"authors\":\"Tan Bui, Yan Naing Tun, Yiran Cheng, Ivana Clairine Irsan, Ting Zhang, Hong Jin Kang\",\"doi\":\"arxiv-2409.05576\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a comprehensive dataset of Java vulnerability-fixing commits\\n(VFCs) to advance research in Java vulnerability analysis. Our dataset, derived\\nfrom thousands of open-source Java projects on GitHub, comprises two variants:\\nJavaVFC and JavaVFC-extended. The dataset was constructed through a rigorous\\nprocess involving heuristic rules and multiple rounds of manual labeling. We\\ninitially used keywords to filter candidate VFCs based on commit messages, then\\nrefined this keyword set through iterative manual labeling. The final labeling\\nround achieved a precision score of 0.7 among three annotators. We applied the\\nrefined keyword set to 34,321 open-source Java repositories with over 50 GitHub\\nstars, resulting in JavaVFC with 784 manually verified VFCs and\\nJavaVFC-extended with 16,837 automatically identified VFCs. Both variants are\\npresented in a standardized JSONL format for easy access and analysis. This\\ndataset supports various research endeavors, including VFC identification,\\nfine-grained vulnerability detection, and automated vulnerability repair. The\\nJavaVFC and JavaVFC-extended are publicly available at\\nhttps://zenodo.org/records/13731781.\",\"PeriodicalId\":501278,\"journal\":{\"name\":\"arXiv - CS - Software Engineering\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.05576\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.05576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

我们提出了一个全面的 Java 漏洞修复提交(VFC)数据集,以推进 Java 漏洞分析研究。我们的数据集来自 GitHub 上的数千个开源 Java 项目,包括两个变体:JavaVFC 和 JavaVFC-extended。该数据集是通过一个严格的过程构建的,其中包括启发式规则和多轮人工标注。我们最初根据提交消息使用关键字来筛选候选 VFC,然后通过迭代手动标注来完善关键字集。在三位标注者的共同努力下,最终的标注精确度达到了 0.7 分。我们将最终确定的关键字集应用于超过 50 个 GitHubstars 的 34,321 个开源 Java 代码库,最终产生了包含 784 个人工验证 VFC 的 JavaVFC 和包含 16,837 个自动识别 VFC 的 JavaVFC-extended。两种变体都以标准化的 JSONL 格式呈现,便于访问和分析。该数据集支持各种研究工作,包括 VFC 识别、细粒度漏洞检测和自动漏洞修复。JavaVFC和JavaVFC-extended可在https://zenodo.org/records/13731781。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
JavaVFC: Java Vulnerability Fixing Commits from Open-source Software
We present a comprehensive dataset of Java vulnerability-fixing commits (VFCs) to advance research in Java vulnerability analysis. Our dataset, derived from thousands of open-source Java projects on GitHub, comprises two variants: JavaVFC and JavaVFC-extended. The dataset was constructed through a rigorous process involving heuristic rules and multiple rounds of manual labeling. We initially used keywords to filter candidate VFCs based on commit messages, then refined this keyword set through iterative manual labeling. The final labeling round achieved a precision score of 0.7 among three annotators. We applied the refined keyword set to 34,321 open-source Java repositories with over 50 GitHub stars, resulting in JavaVFC with 784 manually verified VFCs and JavaVFC-extended with 16,837 automatically identified VFCs. Both variants are presented in a standardized JSONL format for easy access and analysis. This dataset supports various research endeavors, including VFC identification, fine-grained vulnerability detection, and automated vulnerability repair. The JavaVFC and JavaVFC-extended are publicly available at https://zenodo.org/records/13731781.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Promise and Peril of Collaborative Code Generation Models: Balancing Effectiveness and Memorization Shannon Entropy is better Feature than Category and Sentiment in User Feedback Processing Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review A Taxonomy of Self-Admitted Technical Debt in Deep Learning Systems Investigating team maturity in an agile automotive reorganization
×
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