Fetching the paper…
Reading the bibliography…
Writing commit messages is a tedious daily task for many software developers, and often remains neglected.
K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, “BLEU: A method for automatic evaluation of machine translation,” in Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL ’02 . Philadelphia, Pennsylvania: Association for Computational Linguistics, 2001, p. 311
2001
Earlier work this paper cites.
C.-Y. Lin, “Rouge: A package for automatic evaluation of summaries,” in Text Summarization Branches Out , 2004, pp. 74–81
2004
Earlier work this paper cites.
S. Banerjee and A. Lavie, “METEOR: An automatic metric for MT evaluation with improved correlation with human judgments,” in Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization . Ann Arbor, Michigan: Association for Computational Linguistics, Jun. 2005, pp. 65–72
2005
Earlier work this paper cites.
W. Maalej and H.-J. Happel, “Can development work describe itself?” in 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010) , May 2010, pp. 191–200
2010
Earlier work this paper cites.
R. Dyer, H. A. Nguyen, H. Rajan, and T. N. Nguyen, “Boa: A language and infrastructure for analyzing ultra-large-scale software repositories,” in 2013 35th International Conference on Software Engineering (ICSE) , May 2013, pp. 422–431
2013
Earlier work this paper cites.
M. Denkowski and A. Lavie, “Meteor Universal: Language Specific Translation Evaluation for Any Target Language,” in Proceedings of the Ninth Workshop on Statistical Machine Translation . Baltimore, Maryland, USA: Association for Computational Linguistics, 2014, pp. 376–380
2014
Earlier work this paper cites.
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
P. Loyola, E. Marrese-Taylor, and Y. Matsuo, “A Neural Architecture for Generating Natural Language Descriptions from Source Code Changes,” Apr. 2017
2017
Earlier work this paper cites.
X. Hu, G. Li, X. Xia, D. Lo, and Z. Jin, “Deep code comment generation,” in Proceedings of the 26th Conference on Program Comprehension . Gothenburg Sweden: ACM, May 2018, pp. 200–210
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
Z. Liu, X. Xia, A. E. Hassan, D. Lo, Z. Xing, and X. Wang, “Neural-machine-translation-based commit message generation: How far are we?” in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering . Montpellier France: ACM, Sep. 2018, pp. 373–384
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
E. M. Bender and B. Friedman, “Data statements for natural language processing: Toward mitigating system bias and enabling better science,” Transactions of the Association for Computational Linguistics , vol. 6, pp. 587–604, 2018. [Online]. Available: https://aclanthology.org/Q18-1041
2018
Earlier work this paper cites.
M. Post, “A Call for Clarity in Reporting BLEU Scores,” in Proceedings of the Third Conference on Machine Translation: Research Papers . Belgium, Brussels: Association for Computational Linguistics, Oct. 2018, pp. 186–191
2018
Earlier work this paper cites.
Y. Zhu, S. Lu, L. Zheng, J. Guo, W. Zhang, J. Wang, and Y. Yu, “Texygen: A benchmarking platform for text generation models,” in The 41st International ACM SIGIR Conference on Research; Development in Information Retrieval , ser. SIGIR ’18. New York, NY, USA: Association for Computing Machinery, 2018, p. 1097–1100. [Online]. Available: https://doi.org/10.1145/3209978.3210080
2018
Cited alongside, same era.
Q. Liu, Z. Liu, H. Zhu, H. Fan, B. Du, and Y. Qian, “Generating Commit Messages from Diffs using Pointer-Generator Network,” in 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR) . Montreal, QC, Canada: IEEE, May 2019, pp. 299–309
2019
Cited alongside, same era.
S. Xu, Y. Yao, F. Xu, T. Gu, H. Tong, and J. Lu, “Commit Message Generation for Source Code Changes,” in Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence . Macao, China: International Joint Conferences on Artificial Intelligence Organization, Aug. 2019, pp. 3975–3981
2019
Cited alongside, same era.
M. Pravilov, E. Bogomolov, Y. Golubev, and T. Bryksin, “Unsupervised learning of general-purpose embeddings for code changes,” in Proceedings of the 5th International Workshop on Machine Learning Techniques for Software Quality Evolution , ser. MaLTESQuE 2021. New York, NY, USA: Association for Computing Machinery, Aug. 2021, pp. 7–12
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2019
Cited alongside, same era.
M. Allamanis, “The adverse effects of code duplication in machine learning models of code,” in Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software . Athens Greece: ACM, Oct. 2019, pp. 143–153
2019
Cited alongside, same era.
A. Akbik, T. Bergmann, D. Blythe, K. Rasul, S. Schweter, and R. Vollgraf, “FLAIR: An easy-to-use framework for state-of-the-art NLP,” in NAACL 2019, 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations) , 2019, pp. 54–59
2019
Cited alongside, same era.
2020
Cited alongside, same era.
——, “Deep code comment generation with hybrid lexical and syntactical information,” Empirical Software Engineering , vol. 25, no. 3, pp. 2179–2217, May 2020
2020
Cited alongside, same era.
K. Etemadi and M. Monperrus, “On the Relevance of Cross-project Learning with Nearest Neighbours for Commit Message Generation,” Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops , pp. 470–475, Jun. 2020
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2021
Later among the works it cites.
B. Wang, M. Yan, Z. Liu, L. Xu, X. Xia, X. Zhang, and D. Yang, “Quality Assurance for Automated Commit Message Generation,” in 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) , Mar. 2021, pp. 260–271
2021
Later among the works it cites.
Y. Tian, Y. Zhang, K.-J. Stol, L. Jiang, and H. Liu, “What makes a good commit message?” in Proceedings of the 44th International Conference on Software Engineering . Pittsburgh Pennsylvania: ACM, May 2022, pp. 2389–2401
2022
Later among the works it cites.
J. Dong, Y. Lou, Q. Zhu, Z. Sun, Z. Li, W. Zhang, and D. Hao, “FIRA: Fine-grained graph-based code change representation for automated commit message generation,” in Proceedings of the 44th International Conference on Software Engineering , ser. ICSE ’22. New York, NY, USA: Association for Computing Machinery, May 2022, pp. 970–981
2022
Later among the works it cites.
F. Mireshghallah, F. Tramèr, H. Brown, K. Lee, and R. Shokri, “What does it mean for a language model to preserve privacy?” in FaCCT , 2022
2022
Later among the works it cites.
J. A. Rothchild and D. Rothchild, “Copyright implications of the use of code repos- itories to train a machine learning model,” Call for white papers on philosophical and legal questions around Copilot , Feb. 2022. [Online]. Available: https://www.fsf.org/licensing/copilot/copyright-implications-of-the-use-of-code-repositories-to-train-a-machine-learning-model
2022
Later among the works it cites.
A. Eliseeva, Y. Sokolov, E. Bogomolov, Y. Golubev, D. Dig, and T. Bryksin, “From Commit Message Generation to History-Aware Commit Message Completion,” in 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) . Luxembourg, Luxembourg: IEEE, Sep. 2023, pp. 723–735
2023
Later among the works it cites.
N. Muennighoff, Q. Liu, A. Zebaze, Q. Zheng, B. Hui, T. Y. Zhuo, S. Singh, X. Tang, L. von Werra, and S. Longpre, “OctoPack: Instruction Tuning Code Large Language Models,” Aug. 2023
2023
Later among the works it cites.
Getty Images, “Getty Images statement,” https://newsroom.gettyimages.com/en/getty-images/getty-images-statement , Jan. 2023, accessed: 2023-05-22
2023
Later among the works it cites.
M. Butterick, “Github copilot litigation,” https://githubcopilotlitigation.com/ , Nov. 2022, accessed: 2023-05-22
2023
Later among the works it cites.
A. Hern and D. Milmo, “ “I didn’t give permission”
2023
Later among the works it cites.
S. Mukherjee, Y. C. Foo, and M. Coulter, “Eu proposes new copyright rules for generative ai,” https://www.reuters.com/technology/eu-lawmakers-committee-reaches-deal-artificial-intelligence-act-2023-04-27/ , Apr. 2023, accessed: 2023-05-22
2023
Later among the works it cites.
The Italian Data Protection Authority, “Artificial Intelligence: stop to ChatGPT by the Italian SA. Personal data is collected unlawfully, no age verification system is in place for children,” https://www.garanteprivacy.it/home/docweb/-/docweb-display/docweb/9870847 , Mar. 2023, accessed: 2023-05-22
2023
Later among the works it cites.