[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 …
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
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 …
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
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 …
defective ones, which is referred to as the class imbalance problem in software defect …
[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 …
project defect prediction (CPDP). However, some questions still remain. First, the conditional …
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 …
modules. The prediction model's performance is vulnerable to the class imbalance issue in …
[HTML][HTML] 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 …
defect prediction (SDP) has become an important part of software testing. Software defect …
The impact of feature selection techniques on effort‐aware defect prediction: An empirical study
Abstract Effort‐Aware Defect Prediction (EADP) methods sort software modules based on
the defect density and guide the testing team to inspect the modules with high defect density …
the defect density and guide the testing team to inspect the modules with high defect density …
The devil is in the tails: How long-tailed code distributions impact large language models
Learning-based techniques, especially advanced Large Language Models (LLMs) for code,
have gained considerable popularity in various software engineering (SE) tasks. However …
have gained considerable popularity in various software engineering (SE) tasks. However …
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 …
practice. As interpretation from rule-based interpretable models can provide insights about …
Bootstrap aggregation ensemble learning-based reliable approach for software defect prediction by using characterized code feature
To ensure software quality, software defect prediction plays a prominent role for the software
developers and practitioners. Software defect prediction can assist us with distinguishing …
developers and practitioners. Software defect prediction can assist us with distinguishing …