Evaluating the Veracity of Software Bug Reports using Entropy-based Measures

Madhu Kumari, V. B. Singh, Meera Sharma
{"title":"Evaluating the Veracity of Software Bug Reports using Entropy-based Measures","authors":"Madhu Kumari, V. B. Singh, Meera Sharma","doi":"10.4018/ijossp.315280","DOIUrl":null,"url":null,"abstract":"The wide usage of open source software (OSS) results in an increase of bug data forming an integral part of the extensive data ecosystem. This bug report data needs to be analyzed for bug fixing and prediction of various important attributes like bug severity, priority, fix time, assignees, etc. The increased volume of bug data and different bug reporters from different geographical locations make veracity an important concern. We assume that the bug reports (i.e., different bug attributes) reported in software bug repositories are trustworthy during the bug triaging process. In reality, the bug report data are not trustworthy regarding various aspects like integrity, authenticity, and trusted origin as the bugs are reported by users who may or may not have proper knowledge of the software. In this paper, we proposed entropy-based models for veracity estimation of different bug attributes.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"32 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Open Source Software and Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijossp.315280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0

Abstract

The wide usage of open source software (OSS) results in an increase of bug data forming an integral part of the extensive data ecosystem. This bug report data needs to be analyzed for bug fixing and prediction of various important attributes like bug severity, priority, fix time, assignees, etc. The increased volume of bug data and different bug reporters from different geographical locations make veracity an important concern. We assume that the bug reports (i.e., different bug attributes) reported in software bug repositories are trustworthy during the bug triaging process. In reality, the bug report data are not trustworthy regarding various aspects like integrity, authenticity, and trusted origin as the bugs are reported by users who may or may not have proper knowledge of the software. In this paper, we proposed entropy-based models for veracity estimation of different bug attributes.
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
用基于熵的方法评估软件Bug报告的准确性
开源软件(OSS)的广泛使用导致bug数据的增加,这些数据构成了广泛的数据生态系统的一个组成部分。需要对这些bug报告数据进行分析,以便修复bug,并预测各种重要属性,如bug严重性、优先级、修复时间、指派人员等。bug数据量的增加和来自不同地理位置的不同bug报告使得准确性成为一个重要的问题。我们假设在软件bug库中报告的bug报告(例如,不同的bug属性)在bug分类过程中是可信的。实际上,错误报告数据在完整性、真实性和可信来源等各个方面都是不可信的,因为错误是由可能或可能不了解软件的用户报告的。在本文中,我们提出了基于熵的模型来估计不同bug属性的准确性。
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
CiteScore
1.90
自引率
0.00%
发文量
16
期刊介绍: The International Journal of Open Source Software and Processes (IJOSSP) publishes high-quality peer-reviewed and original research articles on the large field of open source software and processes. This wide area entails many intriguing question and facets, including the special development process performed by a large number of geographically dispersed programmers, community issues like coordination and communication, motivations of the participants, and also economic and legal issues. Beyond this topic, open source software is an example of a highly distributed innovation process led by the users. Therefore, many aspects have relevance beyond the realm of software and its development. In this tradition, IJOSSP also publishes papers on these topics. IJOSSP is a multi-disciplinary outlet, and welcomes submissions from all relevant fields of research and applying a multitude of research approaches.
期刊最新文献
Organizational Influencers in Open-Source Software Projects Enhancing Clustering Performance Using Topic Modeling-Based Dimensionality Reduction Cross Project Software Refactoring Prediction Using Optimized Deep Learning Neural Network with the Aid of Attribute Selection Bug Triage Automation Approaches Modelling and Simulation of Patient Flow in the Emergency Department During the COVID-19 Pandemic Using Hierarchical Coloured Petri Net
×
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