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Commit messages aid developers in their understanding of a continuouslyevolving codebase. However, developers not always document code changesproperly. Automatically generating commit messages would relieve this burden ondevelopers. Recently, a number of different works have demonstrated thefeasibility of using methods from neural machine translation to generate commitmessages. This work aims to reproduce a prominent research paper in this field,as well as attempt to improve upon their results by proposing a novelpreprocessing technique. A reproduction of the reference neural machinetranslation model was able to achieve slightly better results on the samedataset. When applying more rigorous preprocessing, however, the performancedropped significantly. This demonstrates the inherent shortcoming of currentcommit message generation models, which perform well by memorizing certainconstructs. Future research directions might include improving diff embeddingsand focusing on specific groups of commits.

Generating Commit Messages from Git Diffs