Computer Science ›› 2017, Vol. 44 ›› Issue (11): 146-155.doi: 10.11896/j.issn.1002-137X.2017.11.022

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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

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

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