StandUp4NPR: Standardizing SetUp for Empirically Comparing Neural Program Repair Systems

Author:

Zhong Wenkang1ORCID,Ge Hongliang1,Ai Hongfei1,Li Chuanyi1,Liu Kui2,Ge Jidong1,Luo Bin1

Affiliation:

1. State Key Laboratory for Novel Software and Technology, Nanjing University, 22 Hankou Road, Nanjing, China, China

2. Huawei Software Engineering Application Technology Lab, China

Funder

National Natural Science Foundation of China (61802167); Natural Science Foundation of Jiangsu Province, China (BK20201250); Cooperation Fund of Huawei-NJU Creative Laboratory for the Next Programming.

Publisher

ACM

Reference66 articles.

1. Dzmitry Bahdanau , Kyunghyun Cho , and Yoshua Bengio . 2015 . Neural Machine Translation by Jointly Learning to Align and Translate . In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http://arxiv.org/abs/1409 .0473 Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http://arxiv.org/abs/1409.0473

2. Berkay Berabi , Jingxuan He , Veselin Raychev , and Martin  T. Vechev . 2021 . TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer . In Proceedings of the 38th International Conference on Machine Learning, ICML 2021 , 18-24 July 2021, Virtual Event(Proceedings of Machine Learning Research, Vol. 139), Marina Meila and Tong Zhang (Eds.). PMLR, 780–791. http://proceedings.mlr.press/v139/berabi21a.html Berkay Berabi, Jingxuan He, Veselin Raychev, and Martin T. Vechev. 2021. TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer. In Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event(Proceedings of Machine Learning Research, Vol. 139), Marina Meila and Tong Zhang (Eds.). PMLR, 780–791. http://proceedings.mlr.press/v139/berabi21a.html

3. Saikat Chakraborty , Yangruibo Ding , Miltiadis Allamanis , and Baishakhi Ray . 2020 . Codit: Code editing with tree-based neural models . IEEE Transactions on Software Engineering( 2020). Saikat Chakraborty, Yangruibo Ding, Miltiadis Allamanis, and Baishakhi Ray. 2020. Codit: Code editing with tree-based neural models. IEEE Transactions on Software Engineering(2020).

4. SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair;Chen Zimin;IEEE Trans. Software Eng.,2021

5. Zimin Chen and Martin Monperrus. 2018. The CodRep Machine Learning on Source Code Competition. CoRR abs/1807.03200(2018). arXiv:1807.03200http://arxiv.org/abs/1807.03200 Zimin Chen and Martin Monperrus. 2018. The CodRep Machine Learning on Source Code Competition. CoRR abs/1807.03200(2018). arXiv:1807.03200http://arxiv.org/abs/1807.03200

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