[HTML][HTML] An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review

NK Nagwani, JS Suri - … Journal of Information Management Data Insights, 2023‏ - Elsevier
The timely release of defect-free software and the optimization of development costs depend
on efficient software bug triaging (SBT) techniques. SBT can also help in managing the vast …

Data quality issues in software fault prediction: a systematic literature review

K Bhandari, K Kumar, AL Sangal - Artificial Intelligence Review, 2023‏ - Springer
Software fault prediction (SFP) aims to improve software quality with a possible minimum
cost and time. Various machine learning models have been proposed in the past for …

Investigation on the stability of SMOTE-based oversampling techniques in software defect prediction

S Feng, J Keung, X Yu, Y **ao, M Zhang - Information and Software …, 2021‏ - Elsevier
Context: In practice, software datasets tend to have more non-defective instances than
defective ones, which is referred to as the class imbalance problem in software defect …

Does data sampling improve deep learning-based vulnerability detection? Yeas! and Nays!

X Yang, S Wang, Y Li, S Wang - 2023 IEEE/ACM 45th …, 2023‏ - ieeexplore.ieee.org
Recent progress in Deep Learning (DL) has sparked interest in using DL to detect software
vulnerabilities automatically and it has been demonstrated promising results at detecting …

Diversity based imbalance learning approach for software fault prediction using machine learning models

P Manchala, M Bisi - Applied Soft Computing, 2022‏ - Elsevier
The Software fault prediction (SFP) target is to distinguish between faulty and non-faulty
modules. The prediction model's performance is vulnerable to the class imbalance issue in …

Software defect prediction based on nested-stacking and heterogeneous feature selection

L Chen, C Wang, S Song - Complex & Intelligent Systems, 2022‏ - Springer
Software testing guarantees the delivery of high-quality software products, and software
defect prediction (SDP) has become an important part of software testing. Software defect …

Fight fire with fire: How much can we trust ChatGPT on source code-related tasks?

X Yu, L Liu, X Hu, JW Keung, J Liu… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
With the increasing utilization of large language models such as ChatGPT during software
development, it has become crucial to verify the quality of code content it generates. Recent …

Improving the undersampling technique by optimizing the termination condition for software defect prediction

S Feng, J Keung, Y **ao, P Zhang, X Yu… - Expert Systems with …, 2024‏ - Elsevier
The class imbalance problem significantly hinders the ability of the software defect
prediction (SDP) models to distinguish between defective (minority class) and non-defective …

Dealing with imbalanced data for interpretable defect prediction

Y Gao, Y Zhu, Y Zhao - Information and software technology, 2022‏ - Elsevier
Context Interpretation has been considered as a key factor to apply defect prediction in
practice. As interpretation from rule-based interpretable models can provide insights about …

[HTML][HTML] A three-stage transfer learning framework for multi-source cross-project software defect prediction

J Bai, J Jia, LF Capretz - Information and Software Technology, 2022‏ - Elsevier
Context Transfer learning techniques have been proved to be effective in the field of Cross-
project defect prediction (CPDP). However, some questions still remain. First, the conditional …