利用开发人员的个人能力和集体责任进行bug分类的联合优化方法

IF 3.8 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information and Software Technology Pub Date : 2025-07-15 DOI:10.1016/j.infsof.2025.107833

Haojie Li , Wei Wei , Jianfei Sui , Guanfeng Liu , Yuying Li , Yang Feng , Junwei Du

{"title":"利用开发人员的个人能力和集体责任进行bug分类的联合优化方法","authors":"Haojie Li , Wei Wei , Jianfei Sui , Guanfeng Liu , Yuying Li , Yang Feng , Junwei Du","doi":"10.1016/j.infsof.2025.107833","DOIUrl":null,"url":null,"abstract":"<div><h3>Context:</h3><div>Efficient bug triage is essential to ensuring the quality of open-source software. Studies have shown that incorporating bug tossing information into bug triage has improved its performance substantially.</div></div><div><h3>Objectives:</h3><div>However, the current bug triage approach that integrates tossing relationships only considers the statistical characteristics of the tossing relationship network or the attribute information of bugs, failing to characterize developers’ capabilities based on tossing network comprehensively. Consequently, various factors, such as developers’ availability, roles within the development organization, and subjective intentions, are overlooked, leading to assigning bugs to developers who are not suited for resolving them. We are attempting to propose an approach to address the above problem.</div></div><div><h3>Methods:</h3><div>We introduces an approach that integrates developers’ <strong>I</strong>ndividual <strong>A</strong>bility with the <strong>C</strong>ollective <strong>R</strong>esponsibility(<strong>IACR</strong>) derived from the bug tossing network. Firstly, we use the text and metadata of the bug reports (including product details, hardware, and components) to define the developer’s individual ability feature. The network structure information learned from tossing network relations also represents the collective responsibility feature. Then we design a joint optimization approach to achieve a better fusion of individual ability and collective responsibility in the form of vector representations.</div></div><div><h3>Results:</h3><div>Experimental results from five datasets indicate that IACR improves the average recommendation accuracy and MRR by 6.94% and 4.72%, respectively, compared to the optimal baselines.</div></div><div><h3>Conclusion:</h3><div>IACR achieves an accurate representation of developers’ capabilities and effectively improves the accuracy of bug triage.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"187 ","pages":"Article 107833"},"PeriodicalIF":3.8000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A joint optimization approach for bug triage leveraging individual ability and collective responsibility of developers\",\"authors\":\"Haojie Li , Wei Wei , Jianfei Sui , Guanfeng Liu , Yuying Li , Yang Feng , Junwei Du\",\"doi\":\"10.1016/j.infsof.2025.107833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Context:</h3><div>Efficient bug triage is essential to ensuring the quality of open-source software. Studies have shown that incorporating bug tossing information into bug triage has improved its performance substantially.</div></div><div><h3>Objectives:</h3><div>However, the current bug triage approach that integrates tossing relationships only considers the statistical characteristics of the tossing relationship network or the attribute information of bugs, failing to characterize developers’ capabilities based on tossing network comprehensively. Consequently, various factors, such as developers’ availability, roles within the development organization, and subjective intentions, are overlooked, leading to assigning bugs to developers who are not suited for resolving them. We are attempting to propose an approach to address the above problem.</div></div><div><h3>Methods:</h3><div>We introduces an approach that integrates developers’ <strong>I</strong>ndividual <strong>A</strong>bility with the <strong>C</strong>ollective <strong>R</strong>esponsibility(<strong>IACR</strong>) derived from the bug tossing network. Firstly, we use the text and metadata of the bug reports (including product details, hardware, and components) to define the developer’s individual ability feature. The network structure information learned from tossing network relations also represents the collective responsibility feature. Then we design a joint optimization approach to achieve a better fusion of individual ability and collective responsibility in the form of vector representations.</div></div><div><h3>Results:</h3><div>Experimental results from five datasets indicate that IACR improves the average recommendation accuracy and MRR by 6.94% and 4.72%, respectively, compared to the optimal baselines.</div></div><div><h3>Conclusion:</h3><div>IACR achieves an accurate representation of developers’ capabilities and effectively improves the accuracy of bug triage.</div></div>\",\"PeriodicalId\":54983,\"journal\":{\"name\":\"Information and Software Technology\",\"volume\":\"187 \",\"pages\":\"Article 107833\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information and Software Technology\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0950584925001727\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information and Software Technology","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0950584925001727","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

摘要

背景：有效的bug分类对于确保开源软件的质量至关重要。研究表明，将bug丢弃信息整合到bug分类中可以大大提高其性能。然而，目前集成抛掷关系的bug分类方法只考虑抛掷关系网络的统计特征或bug的属性信息，未能全面表征基于抛掷网络的开发者能力。因此，各种因素，例如开发人员的可用性、开发组织中的角色和主观意图，都被忽略了，导致将错误分配给不适合解决它们的开发人员。我们正试图提出解决上述问题的方法。方法：引入了一种将开发人员的个人能力与源于bug抛掷网络的集体责任（IACR）相结合的方法。首先，我们使用bug报告的文本和元数据（包括产品细节、硬件和组件）来定义开发人员的个人能力特征。从网络关系中学习到的网络结构信息也表现出集体责任特征。然后，我们设计了一种联合优化方法，以向量表示的形式实现个人能力和集体责任的更好融合。结果：来自5个数据集的实验结果表明，与最优基线相比，IACR的平均推荐准确率和MRR分别提高了6.94%和4.72%。结论：IACR准确地反映了开发人员的能力，有效地提高了bug分类的准确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

A joint optimization approach for bug triage leveraging individual ability and collective responsibility of developers

查看原文本刊更多论文

A joint optimization approach for bug triage leveraging individual ability and collective responsibility of developers

Context:

Efficient bug triage is essential to ensuring the quality of open-source software. Studies have shown that incorporating bug tossing information into bug triage has improved its performance substantially.

Objectives:

However, the current bug triage approach that integrates tossing relationships only considers the statistical characteristics of the tossing relationship network or the attribute information of bugs, failing to characterize developers’ capabilities based on tossing network comprehensively. Consequently, various factors, such as developers’ availability, roles within the development organization, and subjective intentions, are overlooked, leading to assigning bugs to developers who are not suited for resolving them. We are attempting to propose an approach to address the above problem.

Methods:

We introduces an approach that integrates developers’ Individual Ability with the Collective Responsibility(IACR) derived from the bug tossing network. Firstly, we use the text and metadata of the bug reports (including product details, hardware, and components) to define the developer’s individual ability feature. The network structure information learned from tossing network relations also represents the collective responsibility feature. Then we design a joint optimization approach to achieve a better fusion of individual ability and collective responsibility in the form of vector representations.

Results:

Experimental results from five datasets indicate that IACR improves the average recommendation accuracy and MRR by 6.94% and 4.72%, respectively, compared to the optimal baselines.

Conclusion:

IACR achieves an accurate representation of developers’ capabilities and effectively improves the accuracy of bug triage.

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

Information and Software Technology 工程技术-计算机：软件工程

CiteScore

9.10

自引率

7.70%

发文量

164

审稿时长

9.6 weeks

期刊介绍： Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal''s scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include: • Software management, quality and metrics, • Software processes, • Software architecture, modelling, specification, design and programming • Functional and non-functional software requirements • Software testing and verification & validation • Empirical studies of all aspects of engineering and managing software development Short Communications is a new section dedicated to short papers addressing new ideas, controversial opinions, "Negative" results and much more. Read the Guide for authors for more information. The journal encourages and welcomes submissions of systematic literature studies (reviews and maps) within the scope of the journal. Information and Software Technology is the premiere outlet for systematic literature studies in software engineering.