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A large-scale dataset in multi-programming languages and with rich information. This dataset is proposed in the paper "On the Evaluation of Commit Message Generation Models: An Experimental Study" accepted to ICSME 2021 and "A large-scale empirical study of commit message generation: models, datasets and evaluation" accepted to EMSE 2022. Welcome to use our dataset, MCMD, and the evaluation scripts to test the performance of the commit message generation! Citations for these two works can be found here.
commit message, GitHub, Computer Science, Software Engineering
commit message, GitHub, Computer Science, Software Engineering
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 135 | |
| downloads | 124 |

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