Name
Title | ||
|---|---|---|
Within-Project and Cross-Project Just-In-Time Defect Prediction Based on Denoising AutoEncoder and Convolutional Neural Network |
Abstract | ||
|---|---|---|
Just-in-time defect prediction is an important and useful branch in software defect prediction. At present, deep learning is a research hotspot in the field of artificial intelligence, which can combine basic defect features into deep semantic features and make up for the shortcomings of machine learning algorithms. However, the mainstream deep learning techniques have not been applied yet in just... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1049/iet-sen.2019.0278 | IET Software |
Keywords | DocType | Volume |
learning (artificial intelligence),neural nets | Journal | 14 |
Issue | ISSN | Citations |
3 | 1751-8806 | 1 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kun Zhu | 1 | 1 | 1.69 |
| Nana Zhang | 2 | 1 | 1.69 |
| Shi Ying | 3 | 1 | 0.68 |
| Dandan Zhu | 4 | 1 | 1.69 |