J Shanghai Jiaotong Univ Sci ›› 2024, Vol. 29 ›› Issue (3): 566-578.doi: 10.1007/s12204-022-2448-z
YADAV Asmita1, SINGH Kumar Sandeep1,2
收稿日期:
2020-08-24
接受日期:
2021-06-08
出版日期:
2024-05-28
发布日期:
2024-05-28
YADAV Asmita1*, SINGH Kumar Sandeep1,2
Received:
2020-08-24
Accepted:
2021-06-08
Online:
2024-05-28
Published:
2024-05-28
摘要: 在软件开发项目中,漏洞(Bug)是常见的现象。开发者在开源存储库中报告这些漏洞。这需要开发一个高质量的开发者预测模型,该模型应考虑开发者的工作满意度、控制开发成本以及提高漏洞修复时间。当告知新的漏洞时,尽快解决和修复漏洞报告是问题追踪者(Triager)的主要关注点。因此,开发者的工作效率是漏洞修复中的一个重要因素。为了解决这些问题,提出了一种方法,推荐一组可能互相分享知识来修复新漏洞报告的开发者。该方法被称为基于开发者工作效率和社交网络的开发者推荐(DweSn)。它是一个复合模型,通过利用开发者的平均漏洞修复时间、修复各种漏洞的工作效率以及与其他开发者的社交互动来构建开发者的个人档案。在语料库中的新漏洞和已有漏洞之间应用相似度度量,从语料库中提取出有能力解决漏洞的开发者列表。该方法只选择那些活跃且工作负荷较轻的开发者。将具有最高个人档案得分的开发者分配去修复漏洞。在五个大型开源项目(包括Mozilla、Netbeans、Eclipse、Firefox和OpenOffice)的子集上评估了我们的方法,并将其与最新技术进行了比较。结果表明,将开发者的效率、平均漏洞修复时间和他们在社交网络中的互动结合起来,可以提高准确性并有效减少漏洞抛延时间。这种方法在预测准确性、精确度、召回率、F-score和减少漏洞传递长度方面分别提高了93.89%、93.12%、93.46%、93.27%和93.25%。提出的方法达到了93%的命中率和93.34%的平均倒排序值,这表明提出的Triager能够高效地将漏洞分配给正确的开发者。
中图分类号:
YADAV Asmita1, SINGH Kumar Sandeep1,2. 基于时间的自动化多标准缺陷分类方法:开发人员工作效率和基于社交网络的开发人员推荐[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 566-578.
YADAV Asmita1*, SINGH Kumar Sandeep1,2. Automated Time Based Multi-Criteria Bug Triage Approach: Developer Working Efficiency and Social Network Based Developer Recommendation[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 566-578.
[1] JUNG W, LEE E, WU C S. A survey on mining software repositories [J]. IEICE Transactions on Information and Systems, 2012, E95.D(5): 1384-1406. [2] SUREKA A, SINGH H, BAGEWADI M, et al. A decision support platform for guiding a bug triager for resolver recommendation using textual and non-textual features [C]//3rd International Workshop on Quantitative Approaches to Software Quality. New Delhi: CEUR-WS, 2015: 23-30. [3] YANG G, ZHANG T, LEE B. Towards semi-automatic bug triage and severity prediction based on topic model and multi-feature of bug reports [C]/ 2014 IEEE 38th Annual Computer Software and Applications Conference. Vasteras: IEEE, 2014: 97-106. [4] YADAV A, SINGH S K. Survey based classification of bug triage approaches [J]. APTIKOM Journal on Computer Science and Information Technologies, 2016, 1(1): 1-11. [5] XUAN J F, JIANG H, REN Z L, et al. Developer prioritization in bug repositories [C]//34th International Conference on Software Engineering. Zurich: IEEE, 2012: 25-35. [6] ZHANG T, LEE B. An automated bug triage approach: A concept profile and social network based developer recommendation [C]//8th International Conference on Intelligent Computing. Huangshan: Springer, 2012: 505-512. [7] WU W J, ZHANG W, YANG Y, et al. DREX: developer recommendation with K-nearest-neighbor search and expertise ranking [C]//18th Asia-Pacific Software Engineering Conference. Ho Chi Minh City: IEEE, 2011: 389-396. [8] NGUYEN T T, NGUYEN A T, NGUYEN T N. Topicbased, time-aware bug assignment [J]. ACM SIGSOFT Software Engineering Notes, 2014, 39(1): 1-4. [9] PENG X Y, ZHOU P Y, LIU J, et al. Improving bug triage with relevant search [C]//29th International Conference on Software Engineering and Knowledge Engineering. Pittsburgh, PA: IEEE, 2017: 123-128. [10] YANG G, ZHANG T, LEE B. Utilizing a multideveloper network-based developer recommendation algorithm to fix bugs effectively [C]//29th ACM Symposium on Applied Computing. Gyeongju: ACM, 2014: 1134-1139. [11] XIA X, LO D, WANG X Y, et al. Accurate developer recommendation for bug resolution [C]//20th Working Conference on Reverse Engineering. Koblenz: IEEE, 2013: 72-81. [12] XIA X, LO D, WANG X Y, et al. Dual analysis for recommending developers to resolve bugs [J]. Journal of Software: Evolution and Process, 2015, 27(3): 195-220. [13] XIE X H, ZHANG W, YANG Y, et al. DRETOM: developer recommendation based on topic models for bug resolution [C]//8th International Conference on Predictive Models in Software Engineering. Lund: ACM, 2012: 19-28. [14] SHOKRIPOUR R, ANVIK J, KASIRUN Z M, et al. A time-based approach to automatic bug report assignment [J]. Journal of Systems and Software, 2015, 102: 109-122. [15] KUMAR A, GUPTA A. Evolution of developer social network and its impact on bug fixing process [C]//6th India Software Engineering Conference. New Delhi: ACM, 2013: 63-72. [16] BANITAAN S, ALENEZI M. DECOBA: utilizing developers communities in bug assignment [C]//12th International Conference on Machine Learning and Applications. Miami, FL: IEEE, 2013: 66-71. [17] Gephi tool [EB/OL]. [2020-08-24]. https://gephi.org. [18] YADAV A, SINGH S K, SURI J S. Ranking of software developers based on expertise score for bug triaging [J]. Information and Software Technology, 2019, 112: 1-17. |
[1] | . 计算机断层扫描中金属伪影抑制的先验图像改进[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 446-454. |
[2] | . 基于增强现实和超细径摄像头的胸腔闭式引流穿刺可视化系统[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 417-424. |
[3] | 陈坤1, 2, 赵旭1, 董春玉1, 邸子超1, 陈宗枝1. 基于滤波器预测的抗遮挡目标跟踪算法[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 400-413. |
[4] | 邓玉欣1,陈泽众1,汪洋1,杜文杰2,毛碧飞3,梁智章3,林秋诗3,李静辉3. 基于推导树模型的软件可信性推理[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 579-587. |
[5] | 高晓彤1,马艳芳1,2, 周伟1. 基于FAHP-CRITIC方法的软件可信性分析[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 588-600. |
[6] | 曾志贤,曹建军,翁年凤,袁震,余旭. 基于细粒度联合注意力机制的图像-文本跨模态实体分辨[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(6): 728-737. |
[7] | 曹鹤玲a,b,刘方正a,石建树a,楚永贺a,邓淼磊a. 基于随机搜索和代码相似性的程序自动修复[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(6): 738-752. |
[8] | 王培新. 非确定性概率规划的尾界代价分析[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(6): 772-782. |
阅读次数 | ||||||||||||||||||||||||||||||||||||||||||||||||||
全文 29
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||
摘要 151
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||