scholarly journals A novel cross-project software defect prediction algorithm based on transfer learning

2022 ◽  
Vol 27 (1) ◽  
pp. 41-57
Author(s):  
Shiqi Tang ◽  
Song Huang ◽  
Changyou Zheng ◽  
Erhu Liu ◽  
Cheng Zong ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Prediction Algorithm ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Software Defect ◽  
Cross Project

scholarly journals Correlation feature and instance weights transfer learning for cross project software defect prediction

IET Software ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 55-74
Author(s):  
Quanyi Zou ◽  
Lu Lu ◽  
Shaojian Qiu ◽  
Xiaowei Gu ◽  
Ziyi Cai
Keyword(s):  
Transfer Learning ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Software Defect ◽  
Cross Project

Research on Cross-Project Software Defect Prediction Based on Machine Learning

2021 ◽  
pp. 160-165
Author(s):  
Baoping Wang ◽  
Wennan Wang ◽  
Linkai Zhu ◽  
Wenjian Liu
Keyword(s):  
Machine Learning ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Software Defect ◽  
Cross Project

Multiple‐components weights model for cross‐project software defect prediction

IET Software ◽  
2018 ◽  
Vol 12 (4) ◽  
pp. 345-355 ◽  
Author(s):  
Shaojian Qiu ◽  
Lu Lu ◽  
Siyu Jiang
Keyword(s):  
Defect Prediction ◽  
Software Defect Prediction ◽  
Software Defect ◽  
Multiple Components ◽  
Cross Project

An Empirical Study of Ranking-Oriented Cross-Project Software Defect Prediction

2016 ◽  
Vol 26 (09n10) ◽  
pp. 1511-1538 ◽  
Author(s):  
Guoan You ◽  
Feng Wang ◽  
Yutao Ma
Keyword(s):  
Binary Classification ◽  
Learning To Rank ◽  
Classification Problem ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Ranking Problem ◽  
Regression Problem ◽  
Software Defect ◽  
One And Many ◽  
Cross Project

Cross-project defect prediction (CPDP) has recently become very popular in the field of software defect prediction. It was generally treated as a binary classification problem or a regression problem in most of previous studies. However, these existing CPDP methods may be not suitable for those software projects that have limited manpower and budget. To address the issue of priority estimation for buggy software entities, in this paper CPDP is formulated as a ranking problem. Inspired by the idea of the pointwise approach to learning to rank, we propose a ranking-oriented CPDP approach called ROCPDP. A case study conducted on the datasets collected from AEEEM and PROMISE shows that ROCPDP outperforms the eight baseline methods in two CPDP scenarios, namely one-to-one and many-to-one. Besides, in the many-to-one scenario ROCPDP is, by and large, comparable to the best baseline method performed in a specific within-project defect prediction scenario.

Sign in / Sign up

Export Citation Format

Share Document