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Commit messages summarize code changes of each commit in natural language, which help developers understand code changes without digging into detailed implementations and play an essential role in comprehending software evolution. To alleviate human efforts in writing commit messages, researchers have proposed various automated techniques to generate commit messages, including template-based, information retrieval-based, and learning-based techniques. Although promising, previous techniques have limited effectiveness due to their coarse-grained code change representations.

This work proposes a novel commit message generation technique, FIRA, which first represents code changes via fine-grained graphs and then learns to generate commit messages automatically. Different from previous techniques, FIRA represents the code changes with fine-grained graphs, which explicitly describe …