Ismail, Ahmad Muhaimin and Ab Hamid, Siti Hafizah and Sani, Asmiza Abdul and Daud, Nur Nasuha Mohd (2024) Toward Reduction in False Positives Just-In-Time Software Defect Prediction Using Deep Reinforcement Learning. IEEE Access, 12. pp. 47568-47580. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2024.3382991.
Full text not available from this repository.Abstract
Deep Q-Network (DQN) is a popular deep reinforcement learning algorithm that has demonstrated promising results across a variety of domains. DQN presents a promising solution to the challenge of lowering false positives in software defect prediction, thereby enhancing the reliability of the prediction performance. In software defect prediction, false positives occur when the prediction model incorrectly predicts code changes to be defective. Consequently, developers waste time and resources on non-existent defects. This paper advocates for employing DQN in software defect prediction, focusing on minimizing false positives and maximizing the prediction performance. Throughout the training phase, the model learns to predict defect-prone following a reward policy aimed at reducing false results. Experimental findings show that the proposed DQN outperforms baseline classifier, improving the prediction accuracy of true defects by up to 27% when using only 20% efforts. The results show that the effectiveness of DQN in tackling false positives, thereby emphasizing the significance of incorporating dynamic reward in predicting software defects.
| Item Type: | Article |
|---|---|
| Funders: | Universiti Malaya for the Fundamental Research Grant Scheme |
| Uncontrolled Keywords: | Software quality; Predictive models; Codes; Inspection; Costs; Adaptation models; Training; Reinforcement learning; Deep reinforcement learning; Software defect prediction; Deep Q-Network; false positives |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Software Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 13 Nov 2024 04:38 |
| Last Modified: | 13 Nov 2024 04:38 |
| URI: | http://eprints.um.edu.my/id/eprint/45862 |
Actions (login required)
 |
View Item |
