145 citations · 347 across the 20 of their papers we have counts for
6 papers · 1 filter
Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++
Anh The Nguyen, Triet Huynh Minh Le, M. Ali Babar
Background: The C and C++ languages hold significant importance in Software Engineering research because of their widespread use in practice. Numerous studies have utilized Machine…
Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?
Triet H. M. Le, M. Ali Babar
Background: Software Vulnerability (SV) prediction needs large-sized and high-quality data to perform well. Current SV datasets mostly require expensive labeling efforts by experts…
Mitigating Data Imbalance for Software Vulnerability Assessment: Does Data Augmentation Help?
Triet H. M. Le, M. Ali Babar
Background: Software Vulnerability (SV) assessment is increasingly adopted to address the ever-increasing volume and complexity of SVs. Data-driven approaches have been widely used…
Systematic Literature Review on Application of Learning-based Approaches in Continuous Integration
Ali Kazemi Arani, Triet Huynh Minh Le, Mansooreh Zahedi +1
Context: Machine learning (ML) and deep learning (DL) analyze raw data to extract valuable insights in specific phases. The rise of continuous practices in software projects emphas…
Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPT
Triet H. M. Le, M. Ali Babar, Tung Hoang Thai
Background: Software Vulnerability (SV) prediction in emerging languages is increasingly important to ensure software security in modern systems. However, these languages usually h…
Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study
Triet H. M. Le, Xiaoning Du, M. Ali Babar
Collecting relevant and high-quality data is integral to the development of effective Software Vulnerability (SV) prediction models. Most of the current SV datasets rely on SV-fixi…