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 …

Classifying detected software vulnerabilities is an important process. However, the metric
values of security vectors are manually determined by humans, which takes time and may …

Vulnerability prediction refers to the problem of identifying system components that are most
likely to be vulnerable. Typically, this problem is tackled by training binary classifiers on …

With the rate of discovered and disclosed vulnerabilities escalating, researchers have been
experimenting with machine learning to predict whether a vulnerability will be exploited …

Context: Software bug prediction techniques can provide informative guidance in software
engineering practices. Over the past 15 years, developer information has been intensively …

Cyber security has an increasing importance since the day when information technologies
are an invariable part of modern human life. One of the fundamental areas of cyber security …