面向Issue跟踪系统的变更请求报告关闭可能性预测

doi:10.11896/j.issn.1002-137X.2017.11.022

计算机科学 ›› 2017, Vol. 44 ›› Issue (11): 146-155.doi: 10.11896/j.issn.1002-137X.2017.11.022

• 2016 年全国软件与应用学术会议 • 上一篇下一篇

面向Issue跟踪系统的变更请求报告关闭可能性预测

熊文军,张璇,王旭,李彤,尹春林

云南大学软件学院昆明650091,云南大学软件学院昆明650091;云南省软件工程重点实验室昆明650091,云南大学经济学院昆明650091,云南大学软件学院昆明650091;云南省软件工程重点实验室昆明650091,云南大学软件学院昆明650091

出版日期:2018-12-01 发布日期:2018-12-01
基金资助:
本文受国家自然科学基金项目(61502413,5,61379032,4),云南省科技计划项目(2016FB106),云南省教育厅科学研究基金(2015Z020,2013A056),云南省软件工程重点实验室开放基金(2015SE202),云南省创新团队“数据驱动的软件工程创新团队”项目,云南大学高水平创新团队“软件工程创新团队”专项项目,云南大学“中青年骨干教师培养计划”专项项目云南大学人文社科基金(13YNUHSS007)资助

Prediction on Closed-probability of Change Request Report for Issue Tracking System

XIONG Wen-jun, ZHANG Xuan, WANG Xu, LI Tong and YIN Chun-lin

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

摘要/Abstract

摘要： 在Issue跟踪系统中存在大量长期未关闭的变更请求报告,增加了开发者不断点击和阅读这些报告的可能性,严重影响了软件需求管理任务的实施和用户的反馈体验。准确和及时地预测这些报告关闭的可能性或重要性可以提高软件维护任务的质量。定义若干衡量变更请求报告特征的指标,选择在训练数据集上预测效果最佳的指标构建Logistic回归预测模型。使用提出的方法对20个SourceForge项目构成的测试数据集进行实验,得到平均查全率为94%和平均伪正率为14%的结果。实验结果表明,提出的方法能在测试数据集上取得很好的预测性能；关闭状态的变更请求报告所占的百分比或数量大小并不影响模型的性能；变更请求报告具有的某些特征可用于预测其在下一版本中得到关闭的可能性。

关键词: 变更请求报告,软件需求,缺陷报告,报告优先级

Abstract: There are lots of change request reports without being closed for a long time in the Issue tracking system,which increases the likelihood of developers to click and read the reports again and again.It seriously affects the imple-mentation of management task of software requirements and the feedback experiences of users.The accurate and instant prediction of closed-probability or importance of these reports can improve the quality of the task of software maintenance.Several metrics were defined to measure the feature of change request,and Logistic regression prediction model was built by using these best predictive metrics on datasets for training.Then experiments which applied proposed method were performed on datasets of testing which contain 20 SourceForge projects,and achieved a result that average recall of 95% and average FPR (False Positive Rate) of 14%.Analysis of experimental result shows that the proposed method can achieve a good prediction performance on datasets of testing,and closed-percentage or size of change requests report doesn’t affect the performance of the model,and some features of change request report can be used to predict its closed-probability in the next version.

Key words: Change request report,Software requirement,Bug report,Prioritization of report

熊文军,张璇,王旭,李彤,尹春林. 面向Issue跟踪系统的变更请求报告关闭可能性预测[J]. 计算机科学, 2017, 44(11): 146-155. https://doi.org/10.11896/j.issn.1002-137X.2017.11.022

XIONG Wen-jun, ZHANG Xuan, WANG Xu, LI Tong and YIN Chun-lin. Prediction on Closed-probability of Change Request Report for Issue Tracking System[J]. Computer Science, 2017, 44(11): 146-155. https://doi.org/10.11896/j.issn.1002-137X.2017.11.022

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面向Issue跟踪系统的变更请求报告关闭可能性预测

Prediction on Closed-probability of Change Request Report for Issue Tracking System

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