Automated Metric Visualizations for Analyzing Source Code Repositories
Jaekwon Lee, Woo-Sung Jung · 2013
Nowadays, the size of information from software projects are overwhelming developers and maintainers. Thus, researchers have studied to extract useful knowledge from the source code repositories. However, it is difficult to find patterns or trends from the text-style data directly. In this paper, we propose an automated approach to visualize the metrics of multiple projects. The case studies with the Android open source projects from v1.6 to v4.2 show that outliers, patterns or trends of code changes can be effectively detected with our approach.