计算机科学 ›› 2016, Vol. 43 ›› Issue (11): 246-251.doi: 10.11896/j.issn.1002-137X.2016.11.048

• 软件与数据库技术 • 上一篇    下一篇

基于缺陷相似度与再分配图的软件缺陷分配方法

史高翔,赵逢禹   

  1. 上海理工大学光电信息与计算机工程学院 上海200093,上海理工大学光电信息与计算机工程学院 上海200093
  • 出版日期:2018-12-01 发布日期:2018-12-01

Software Defect Assignment Method Based on Defect Similarity and Tossing Graph

SHI Gao-xiang and ZHAO Feng-yu   

  • Online:2018-12-01 Published:2018-12-01

摘要: 准确地将缺陷分配给最合适的修复者对大型软件项目的缺陷修复具有重要意义。当前缺陷自动分配技术的研究主要利用历史缺陷报告的描述信息、缺陷关联信息、历史分派信息等,但这些方法都没有将缺陷报告信息充分挖掘。提出在缺陷报告分配时将缺陷历史分派信息和缺陷文本相似信息相结合。首先根据缺陷历史分派信息生成再分配图;然后计算新缺陷报告与历史缺陷报告缺陷的文本相似度,找出相似度最高的前K个缺陷报告所对应的修复者;最后,根据这些修复者在再分配图中的依赖关系生成预测再分配路径。为了验证该方法的有效性,利用Eclipse和Mozilla的缺陷报告集进行实验,实验表明提出的方法在预测的准确度上明显优于其他方法。

关键词: 历史缺陷报告,缺陷相似度,再分配图,预测再分配路径

Abstract: It has important significance to assign a bug report to the most suitable developer to repair in large software projects.At present,there are some methods using in automatic distribution for bug reports,such as utilizing description information of the historical bug reports,associating of bug reports,and historical information of bug report assignment.However,these methods do not fully exploit the information of defect report.This paper proposed to combine historical repair information with history assignment information.Firstly,a tossing graph is built up based on historical information of bug report assignment.Secondly,the similarity of new bug reports and historical bug reports is calculated,and the K final solvers who are corresponding to the K bug reports which have the highest similarity to the new bug report are selected.Finally,according to the dependent relations of these solvers in the tossing graph,a prediction assignment path is generated.To verify the validity of this method,we performed experiments with Eclipse and Mozilla defect report set.Experiments show that the method we proposed is superior to other methods in the accuracy of prediction.

Key words: Historical bug report,Defect similarity,Tossing graph,Predicted assignment path

[1] Jeong G,Kim S,Zimmermann T.Improving bug triage withbugtossing graphs[C]∥Proceedings of the 7th Joint Meeting of the European software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering on European Software Engineering Conference and Foundations of Software Engineering Symposium.ACM,2009:111-120
[2] Cubranic D,Murphy G C.Automatic bug triage using text categorization[C]∥Proceedings of the International Conference on Software Engineering & Knowledge Engineering.Alberta,2004:92-97
[3] Anvik J,Hiew L,Murphy G.Who should fix this bug? [C]∥Proceedings of the 28th International Conference on Software Engineering.ACM,2006:361-370
[4] Xuan J,Jiang H,Ren Z,et al.Automatic bug triage using semi-supervised text classification[C]∥Proceedings of International Conference on Software Enginee-ring & Knowledge Engineering.Redwood City,2010:209-214
[5] Podgurski A,Leon D,Francis P.Automated support for classify software failure report[C]∥Proceedings 25th International Conference on Software Engineering.IEEE,2003:465-475
[6] Matter D,Kuhn A,Nierstrasz O.Assigning bug reports using a vocabulary-based expertise model of developers[C]∥6th IEEE International Working Conference Mining Software Repositories(MSR’09).2009:131-140
[7] Bhattacharya P,Neamtiu I.Fine-grained incremental learningand multi-feature tossing graphs to improve bugtriaging[C]∥Proceedings of the IEEE International Conference on Software Maintenance.Timisoara,2010:1-10
[8] Chen Li-guo,Wang Xiao-bo,Liu Chao.Improving Bug Assignment whit Bug Tossing Graphs and Bug Similarities [J].Journal of Software,2011,6(3):421-427
[9] Pang Jian-feng,Bu Dong-bo,Bai Suo.Automatic text classification system based on vector space model of the research and implement.[J].Computer Application Resarch,2001,4(9):23-26(in Chinese) 庞尖峰,卜东波,白硕.基于向量空间模型的文本自动分类系统的研究与实现[J].计算机应用研究,2001,4(9):23-26
[10] Li Yuan-yuan,Ma Yong-qiang.The weight of text’s trait word calculate method base on Latent semantic indexing[J].Compu-ter Application,2008,8(6):1460-1464(in Chinese) 李媛媛,马永强.基于潜在语义索引的文本特征词权重计算方法[J].计算机应用,2008,28(6):1460-1464
[11] Pang Guo-qing.Using word piece as trait calculate text similarity in VSM[J].Computer and Digital Engineering,2007,5(10):24-36(in Chinese) 潘国清.VSM中用语片为特征项计算文本相似度[J].计算机与数字工程,2007,5(10):24-36
[12] Pang Guo-qing.An improved method and application about trait word extract [J].Journal of Hunan College of Engineering,2009,9(2):38-41(in Chinese) 潘国清.一种向量空间模型种对特征项的改进方法及应用[J].湖南工程学院学报,2009,9(2):38-41

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!