| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4972204 | Information and Software Technology | 2017 | 16 Pages |
Abstract
Our method discovers that it is effective for building change-prone class prediction model by using unsupervised method. It is convenient for practical usage in industry, since it does not need prior labeled data.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Human-Computer Interaction
Authors
Yan Meng, Zhang Xiaohong, Liu Chao, Xu Ling, Yang Mengning, Yang Dan,