Change-Prone Java Method Prediction by Focusing on Individual Differences in Comment Density

Abstract

This paper focuses on differences in comment densities among individual programmers, and proposes to adjust the conventional code complexity metric (the cyclomatic complexity) by using the abnormality of the comment density. An empirical study with nine popular open source Java products (including 103,246 methods) shows that the proposed metric performs better than the conventional one in predicting change-prone methods; the proposed metric improves the area under the ROC curve (AUC) by about 3.4% on average.