Separating signal from noise in coding evaluations

To improve coding evaluations, researchers found that separating signal from noise in code reviews is crucial. They proposed a method to identify high-quality code changes. This matters because it can help developers focus on meaningful changes and reduce noise. To apply this, use machine learning models to analyze code changes and identify signal.