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Detecting and Untangling Composite Commits via Attributed graph Modeling

JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 2025年第1期40卷 119-137页

作者： Xu, Sheng-Bin Chen, Si-Yu Yao, Yuan Xu, Feng Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Peoples R China

During software development, developers tend to tangle multiple concerns into a single commit, resulting in many composite commits. This paper studies the problem of detecting and untangling composite commits, so as to improve the maintainability and understandability of software. Our approach is built upon the observation that both the textual content of code statements and the dependencies between code statements are helpful in comprehending the code commit. Based on this observation, we first construct an attributed graph for each commit, where code statements and various code dependencies are modeled as nodes and edges, respectively, and the textual bodies of code statements are maintained as node attributes. Based on the attributed graph, we propose graph-based learning algorithms that first detect whether the given commit is a composite commit, and then untangle the composite commit into atomic ones. We evaluate our approach on nine C# projects, and the results demonstrate the effectiveness and efficiency of our approach.

关键词： composite commit commit untangling code dependency graph attributed graph

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Untangling Composite Commits by Attributed graph Clustering 22

Untangling Composite Commits by Attributed Graph Clustering

引用

13th Asia-Pacific Symposium on Internetware (Internetware) - A Software Paradigm for Internet Computing

作者： Chen, Siyu Xu, Shengbin Yao, Yuan Xu, Feng Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9781450397803

During software development, it is considered to be a best practice if each commit represents one distinct concern, such as fixing a bug or adding a new feature. However, developers may not always follow this practice and sometimes tangle multiple concerns into a single composite commit. This makes automatic commit untangling a necessary task, and recent approaches mainly untangle commits via applying graph clustering on the code dependency graph. In this paper, we propose a new commit untangling approach, COMUNT, to decompose the composite commits into atomic ones. Different from existing approaches, COMUNT is built upon the observation that both the textual content of code statements and the dependencies between code statements contain useful semantic information so as to better comprehend the committed code changes. Based on this observation, COMUNT first constructs an attributed graph for each commit, where code statements and various code dependencies are modeled as nodes and edges, respectively, and the textual body of code statements are maintained as node attributes. It then conducts attributed graph clustering on the constructed graph. The used attributed graph clustering algorithm can simultaneously encode both graph structure and node attributes so as to better separate the code changes into clusters with distinct concerns. We evaluate our approach on nine C# projects, and the experimental result shows that COMUNT improves the state-of-the-art by 7.8% in terms of untangling accuracy, and meanwhile it is more than 6 times faster.

关键词： Commit untangling code dependency graph attributed graph clustering

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