合并源代码作者、维护者和变更倾向,对变更请求进行分类

Kamal Hossen, H. Kagdi, D. Poshyvanyk
{"title":"合并源代码作者、维护者和变更倾向,对变更请求进行分类","authors":"Kamal Hossen, H. Kagdi, D. Poshyvanyk","doi":"10.1145/2597008.2597147","DOIUrl":null,"url":null,"abstract":"The paper presents an approach, namely iMacPro, to recommend developers who are most likely to implement incoming change requests. iMacPro amalgamates the textual similarity between the given change request and source code, change proneness information, authors, and maintainers of a software system. Latent Semantic Indexing (LSI) and a lightweight analysis of source code, and its commits from the software repository, are used. The basic premise of iMacPro is that the authors and maintainers of the relevant source code, which is change prone, to a given change request are most likely to best assist with its resolution. iMacPro unifies these sources in a unique way to perform its task, which was not investigated and reported in the literature previously. \n An empirical study on three open source systems, ArgoUML, JabRef, and jEdit , was conducted to assess the effectiveness of iMacPro. A number of change requests from these systems were used in the evaluated benchmark. Recall values for top one, five, and ten recommended developers are reported. Furthermore, a comparative study with a previous approach that uses the source-code authorship information for developer recommendation was performed. Results show that iMacPro could provide recall gains from 30% to 180% over its subjected competitor with statistical significance.","PeriodicalId":6853,"journal":{"name":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","volume":"14 1","pages":"130-141"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Amalgamating source code authors, maintainers, and change proneness to triage change requests\",\"authors\":\"Kamal Hossen, H. Kagdi, D. Poshyvanyk\",\"doi\":\"10.1145/2597008.2597147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents an approach, namely iMacPro, to recommend developers who are most likely to implement incoming change requests. iMacPro amalgamates the textual similarity between the given change request and source code, change proneness information, authors, and maintainers of a software system. Latent Semantic Indexing (LSI) and a lightweight analysis of source code, and its commits from the software repository, are used. The basic premise of iMacPro is that the authors and maintainers of the relevant source code, which is change prone, to a given change request are most likely to best assist with its resolution. iMacPro unifies these sources in a unique way to perform its task, which was not investigated and reported in the literature previously. \\n An empirical study on three open source systems, ArgoUML, JabRef, and jEdit , was conducted to assess the effectiveness of iMacPro. A number of change requests from these systems were used in the evaluated benchmark. Recall values for top one, five, and ten recommended developers are reported. Furthermore, a comparative study with a previous approach that uses the source-code authorship information for developer recommendation was performed. Results show that iMacPro could provide recall gains from 30% to 180% over its subjected competitor with statistical significance.\",\"PeriodicalId\":6853,\"journal\":{\"name\":\"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)\",\"volume\":\"14 1\",\"pages\":\"130-141\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2597008.2597147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2597008.2597147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32

摘要

本文提出了一种方法,即iMacPro,来推荐最有可能实现传入变更请求的开发人员。iMacPro合并了给定变更请求和源代码、变更倾向信息、作者和软件系统维护者之间的文本相似性。使用了潜在语义索引(LSI)和源代码的轻量级分析,并从软件存储库提交。iMacPro的基本前提是,对于给定的变更请求,相关源代码的作者和维护者(容易发生变更)最有可能最好地协助解决变更请求。iMacPro以一种独特的方式统一这些来源来执行其任务,这在以前的文献中没有调查和报道。通过对ArgoUML、JabRef和jEdit三个开源系统的实证研究,对iMacPro的有效性进行了评估。在评估的基准中使用了来自这些系统的许多更改请求。报告前1、5和10名推荐开发人员的召回值。此外,还与之前使用源代码作者信息进行开发人员推荐的方法进行了比较研究。结果表明,iMacPro的召回率比竞争对手提高了30% ~ 180%,具有统计学意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Amalgamating source code authors, maintainers, and change proneness to triage change requests
The paper presents an approach, namely iMacPro, to recommend developers who are most likely to implement incoming change requests. iMacPro amalgamates the textual similarity between the given change request and source code, change proneness information, authors, and maintainers of a software system. Latent Semantic Indexing (LSI) and a lightweight analysis of source code, and its commits from the software repository, are used. The basic premise of iMacPro is that the authors and maintainers of the relevant source code, which is change prone, to a given change request are most likely to best assist with its resolution. iMacPro unifies these sources in a unique way to perform its task, which was not investigated and reported in the literature previously. An empirical study on three open source systems, ArgoUML, JabRef, and jEdit , was conducted to assess the effectiveness of iMacPro. A number of change requests from these systems were used in the evaluated benchmark. Recall values for top one, five, and ten recommended developers are reported. Furthermore, a comparative study with a previous approach that uses the source-code authorship information for developer recommendation was performed. Results show that iMacPro could provide recall gains from 30% to 180% over its subjected competitor with statistical significance.
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
×
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:604180095
Book学术官方微信