How Lightweight ML Models Predict Vulnerable Code Changes

This article outlines a lightweight machine-learning framework designed to classify vulnerability-prone code changes using six common classifiers and a rich set of feature types spanning human behavior, code complexity, review patterns, historical vulnerability data, process trends, and text-mined code tokens.