Deepcva: Automated commit-level vulnerability assessment with deep multi-task learning
It is increasingly suggested to identify Software Vulnerabilities (SVs) in code commits to give
early warnings about potential security risks. However, there is a lack of effort to assess …
early warnings about potential security risks. However, there is a lack of effort to assess …
[HTML][HTML] VALIDATE: A deep dive into vulnerability prediction datasets
Context: Vulnerabilities are an essential issue today, as they cause economic damage to the
industry and endanger our daily life by threatening critical national security infrastructures …
industry and endanger our daily life by threatening critical national security infrastructures …
DeepCPDP: Deep learning based cross-project defect prediction
Cross-project defect prediction (CPDP) is an active research topic in the domain of software
defect prediction, since CPDP can be applied to the following scenarios: the target project …
defect prediction, since CPDP can be applied to the following scenarios: the target project …
A Systematic Literature Review on Software Vulnerability Prediction Models
The prediction of software vulnerability requires crucial awareness during the software
specification, design, development, and configuration to achieve less vulnerable and secure …
specification, design, development, and configuration to achieve less vulnerable and secure …
The impact factors on the performance of machine learning-based vulnerability detection: A comparative study
Abstract Machine learning-based Vulnerability detection is an active research topic in
software security. Different traditional machine learning-based and deep learning-based …
software security. Different traditional machine learning-based and deep learning-based …
ALTRA: Cross-project software defect prediction via active learning and tradaboost
Cross-project defect prediction (CPDP) methods can be used when the target project is a
new project or lacks enough labeled program modules. In these new target projects, we can …
new project or lacks enough labeled program modules. In these new target projects, we can …
Efficient feature selection for static analysis vulnerability prediction
Common software vulnerabilities can result in severe security breaches, financial losses,
and reputation deterioration and require research effort to improve software security. The …
and reputation deterioration and require research effort to improve software security. The …
A comprehensive investigation of the impact of feature selection techniques on crashing fault residence prediction models
Context: Software crash is a serious form of the software failure, which often occurs during
the software development and maintenance process. As the stack trace reported when the …
the software development and maintenance process. As the stack trace reported when the …
On the coordination of vulnerability fixes: An empirical study of practices from 13 CVE numbering authorities
Abstract The Common Vulnerabilities and Exposures (CVE) program is dedicated to
analyzing vulnerabilities, then to assigning a unique ID to them and disclosing the …
analyzing vulnerabilities, then to assigning a unique ID to them and disclosing the …
Understanding in-app advertising issues based on large scale app review analysis
Context: In-app advertising closely relates to app revenue. Reckless ad integration could
adversely impact app quality and user experience, leading to loss of income. It is very …
adversely impact app quality and user experience, leading to loss of income. It is very …