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[HTML][HTML] An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review
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 …
Does data sampling improve deep learning-based vulnerability detection? Yeas! and Nays!
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 …
vulnerabilities automatically and it has been demonstrated promising results at detecting …
Diversity based imbalance learning approach for software fault prediction using machine learning models
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 …
Software defect prediction based on nested-stacking and heterogeneous feature selection
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 …
Fight fire with fire: How much can we trust ChatGPT on source code-related tasks?
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 …
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
The class imbalance problem significantly hinders the ability of the software defect
prediction (SDP) models to distinguish between defective (minority class) and non-defective …
prediction (SDP) models to distinguish between defective (minority class) and non-defective …
Dealing with imbalanced data for interpretable defect prediction
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 …
[HTML][HTML] A three-stage transfer learning framework for multi-source cross-project software defect prediction
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 …