Background: Software Vulnerability (SV) prediction in emerging languages is increasingly
important to ensure software security in modern systems. However, these languages usually …

Background: Software Vulnerability (SV) assessment is increasingly adopted to address the
ever-increasing volume and complexity of SVs. Data-driven approaches have been widely …

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 …

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-fixing …

Background: The C/C++ languages hold significant importance in Software Engineering
research because of their widespread use in practice. Numerous studies have utilized …

Security misconfigurations in Container Orchestrators (COs) can pose serious threats to
software systems. While Static Analysis Tools (SATs) can effectively detect these security …

Software vulnerabilities are flaws that may be exploited to cause loss or harm. Various
automated machine-learning techniques have been developed in preceding studies to …

Software security faces critical challenges in the digital age with risks from vulnerabilities like
buffer overflow, software supply chain threats, and adversarial attacks leading to severe …