4 citations · 10 across the 6 of their papers we have counts for
5 papers · 1 filter
An Empirical Study of the Imbalance Issue in Software Vulnerability Detection
Yuejun Guo, Qiang Hu, Qiang Tang +1
Vulnerability detection is crucial to protect software security. Nowadays, deep learning (DL) is the most promising technique to automate this detection task, leveraging its superi…
MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentation
Zeming Dong, Qiang Hu, Yuejun Guo +5
Inspired by the great success of Deep Neural Networks (DNNs) in natural language processing (NLP), DNNs have been increasingly applied in source code analysis and attracted signifi…
Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation
Qiang Hu, Yuejun Guo, Xiaofei Xie +4
Deep learning (DL) plays a more and more important role in our daily life due to its competitive performance in industrial application domains. As the core of DL-enabled systems, d…
CodeS: Towards Code Model Generalization Under Distribution Shift
Qiang Hu, Yuejun Guo, Xiaofei Xie +4
Distribution shift has been a longstanding challenge for the reliable deployment of deep learning (DL) models due to unexpected accuracy degradation. Although DL has been becoming…
An Extensive Systematic Review on Model-Driven Development of Secure Systems
Phu H. Nguyen, Max Kramer, Jacques Klein +1
Context: Model-Driven Security (MDS) is as a specialised Model-Driven Engineering research area for supporting the development of secure systems. Over a decade of research on MDS h…