Evaluating Explanations for Software Patches Generated by Large Language Models

Author:

Sobania DominikORCID,Geiger AlinaORCID,Callan JamesORCID,Brownlee AlexanderORCID,Hanna CarolORCID,Moussa RebeccaORCID,López Mar ZamoranoORCID,Petke JustynaORCID,Sarro FedericaORCID

Publisher

Springer Nature Switzerland

Reference12 articles.

1. Chen, E., Huang, R., Chen, H.S., Tseng, Y.H., Li, L.Y.: GPTutor: a ChatGPT-powered programming tool for code explanation. arXiv preprint arXiv:2305.01863 (2023)

2. Chen, M., et al.: Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021)

3. Fan, A., et al.: Large language models for software engineering: survey and open problems (2023)

4. Just, R., Jalali, D., Ernst, M.D.: Defects4J: a database of existing faults to enable controlled testing studies for Java programs. In: Proceedings of the 2014 International Symposium on Software Testing and Analysis, pp. 437–440. ISSTA 2014, Association for Computing Machinery, New York, NY, USA (2014)

5. Kaddour, J., Harris, J., Mozes, M., Bradley, H., Raileanu, R., McHardy, R.: Challenges and applications of large language models. arXiv preprint arXiv:2307.10169 (2023)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Large Language Models for Software Engineering: Survey and Open Problems;2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE);2023-05-14

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