Predicting Bug Estimation Time for Newly Reported Bug Using Machine Learning Algorithms

被引：3
|
作者：
Sawarkar, Rucha [1 ]
Nagwani, Naresh Kumar [2 ]
Kumar, Sanjay [1 ]
机构：
[1] NIT Raipur, Dept Informat Technol, Chattisgarh, India
[2] NIT Raipur, Dept Comp Sci & Engn, Chattisgarh, India
来源：
2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT) | 2019年
关键词：
Software bug Repositories; bug estimation; Machine learning Algorithms;
D O I：
10.1109/i2ct45611.2019.9033749
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In commercial projects, number of defects raised directly depends upon the releases. In order to get the idea of progress of the project it is necessary to estimate the average time required to fix the bug. This time is referred as bug estimation time. It is essential to estimate the time of software bug for a proper project planning. In this paper, a new algorithm is proposed to determine bug estimation time with the help of machine learning algorithms. New developer is predicted and its average bug estimation time is calculated based on the bug estimation time of already existing developer. A comparative study for accuracy for different machine learning algorithms is carried out.
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页数：4
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