重构bug和测试用例之间的可追溯性:一项实验研究

Nilam Kaushik, L. Tahvildari, Mark Moore
{"title":"重构bug和测试用例之间的可追溯性:一项实验研究","authors":"Nilam Kaushik, L. Tahvildari, Mark Moore","doi":"10.1109/WCRE.2011.58","DOIUrl":null,"url":null,"abstract":"In manual testing, testers typically follow the steps listed in the bug report to verify whether a bug has been fixed or not. Depending on time and availability of resources, a tester may execute some additional test cases to ensure test coverage. In the case of manual testing, the process of finding the most relevant manual test cases to run is largely manual and involves tester expertise. From a usability standpoint, the task of finding the most relevant test cases is tedious as the tester typically has to switch between the defect management tool and the test case management tool in order to search for test cases relevant to the bug at hand. In this paper, we use IR techniques to recover trace ability between bugs and test cases with the aim of recommending test cases for bugs. We report on our experience of recovering trace ability between bugs and test cases using techniques such as Latent Semantic Indexing (LSI) and Latent Dirichlet Allocation (LDA) through a small industrial case study.","PeriodicalId":350863,"journal":{"name":"2011 18th Working Conference on Reverse Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Reconstructing Traceability between Bugs and Test Cases: An Experimental Study\",\"authors\":\"Nilam Kaushik, L. Tahvildari, Mark Moore\",\"doi\":\"10.1109/WCRE.2011.58\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In manual testing, testers typically follow the steps listed in the bug report to verify whether a bug has been fixed or not. Depending on time and availability of resources, a tester may execute some additional test cases to ensure test coverage. In the case of manual testing, the process of finding the most relevant manual test cases to run is largely manual and involves tester expertise. From a usability standpoint, the task of finding the most relevant test cases is tedious as the tester typically has to switch between the defect management tool and the test case management tool in order to search for test cases relevant to the bug at hand. In this paper, we use IR techniques to recover trace ability between bugs and test cases with the aim of recommending test cases for bugs. We report on our experience of recovering trace ability between bugs and test cases using techniques such as Latent Semantic Indexing (LSI) and Latent Dirichlet Allocation (LDA) through a small industrial case study.\",\"PeriodicalId\":350863,\"journal\":{\"name\":\"2011 18th Working Conference on Reverse Engineering\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 18th Working Conference on Reverse Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCRE.2011.58\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 18th Working Conference on Reverse Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCRE.2011.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

摘要

在手动测试中,测试人员通常按照错误报告中列出的步骤来验证错误是否已经修复。根据时间和资源的可用性,测试人员可以执行一些额外的测试用例来确保测试覆盖率。在手工测试的情况下,寻找最相关的手工测试用例运行的过程在很大程度上是手工的,并且涉及测试人员的专业知识。从可用性的角度来看,寻找最相关的测试用例的任务是乏味的,因为测试人员通常必须在缺陷管理工具和测试用例管理工具之间切换,以便搜索与手头的bug相关的测试用例。在本文中,我们使用IR技术来恢复bug和测试用例之间的跟踪能力,目的是为bug推荐测试用例。我们通过一个小型工业案例研究,报告了我们使用潜在语义索引(LSI)和潜在狄利克雷分配(LDA)等技术在bug和测试用例之间恢复追踪能力的经验。
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
Reconstructing Traceability between Bugs and Test Cases: An Experimental Study
In manual testing, testers typically follow the steps listed in the bug report to verify whether a bug has been fixed or not. Depending on time and availability of resources, a tester may execute some additional test cases to ensure test coverage. In the case of manual testing, the process of finding the most relevant manual test cases to run is largely manual and involves tester expertise. From a usability standpoint, the task of finding the most relevant test cases is tedious as the tester typically has to switch between the defect management tool and the test case management tool in order to search for test cases relevant to the bug at hand. In this paper, we use IR techniques to recover trace ability between bugs and test cases with the aim of recommending test cases for bugs. We report on our experience of recovering trace ability between bugs and test cases using techniques such as Latent Semantic Indexing (LSI) and Latent Dirichlet Allocation (LDA) through a small industrial case study.
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
Reverse Engineering Co-maintenance Relationships Using Conceptual Analysis of Source Code Renovation by Machine-Assisted Program Transformation in Production Reporting and Integration Reasoning over the Evolution of Source Code Using Quantified Regular Path Expressions An Exploratory Study of Software Reverse Engineering in a Security Context Analyzing the Source Code of Multiple Software Variants for Reuse Potential
×
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