CoRA: Decomposing and Describing Tangled Code Changes for Reviewer

Code review is an important mechanism for code quality assurance both in open source software and industrial software. Reviewers usually suffer from numerous, tangled and loosely related code changes that are bundled in a single commit, which makes code review very difficult. In this paper, we propose CoRA (Code Review Assistant), an automatic approach to decompose a commit into different parts and generate concise descriptions for reviewers. More specifically, CoRA can decompose a commit into independent parts (e.g., bug fixing, new feature adding, or refactoring) by code dependency analysis and tree-based similar-code detection, then identify the most important code changes in each part based on the PageRank algorithm and heuristic rules. As a result, CoRA can generate a concise description for each part of the commit. We evaluate our approach in seven open source software projects and 50 code commits. The results indicate that CoRA can improve the accuracy of decomposing code changes by 6.3% over the state-ofart practice. At the same time, CoRA can identify the important part from the fine-grained code changes with a mean average precision (MAP) of 87.7%. We also conduct a human study with eight participants to evaluate the performance and usefulness of CoRA, the user feedback indicates that CoRA can effectively help reviewers.