Just-in-Time Prediction of Software Architectural Changes Through Commit-Level Analyses

During software evolution, commits with various purposes, such as bug fixes, feature additions, improvements, etc., are continuously applied to software systems. This could drift software architecture from its planned design, and even cause architectural decay, that negatively affects software maintenance. Although prior studies have presented that even daily code commits could induce architectural changes, and the commit-level analysis has been widely used for multiple software comprehension and maintenance tasks, there is little work analyzing the architectural changes at the commit level. To bridge this gap, we conduct a study investigating the relationships between commits and architectural changes. Through our evaluation of thirty projects, we have shown that the architecture remains stable after most of the commits. However, there still exists a large portion of commits (27% of all studied commits) that have induced architectural changes, which deserve more attention. This further suggests the importance of analyzing architectural changes at the commit level. Meanwhile, we present a suite of commit-level metrics strongly correlated with architectural changes. Finally, we propose prediction models that can effectively forecast how much of the architecture would be changed after a commit.