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Large Language Models for Software Engineering: Survey and Open Problems

  • Published:2023-05-14 Issue: Volume: Page:
  • ISSN:
  • Container-title:2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE)
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Author:

Fan Angela1,Gokkaya Beliz2,Harman Mark3,Lyubarskiy Mitya4,Sengupta Shubho5,Yoo Shin6,Zhang Jie M.7

Affiliation:

1. Generative AI Team Meta Platforms Inc.,New York,NY,USA

2. PyTorch Team Meta Platforms Inc.,Menlo Park,CA,USA

3. Instagram Product Foundation Meta Platforms Inc.,London,UK

4. Developer Infrastructure Meta Platforms Inc.,London,UK

5. FAIR Meta Platforms Inc.,Menlo Park,CA,USA

6. School of Computing KAIST,Daejeon,Korea

7. King's College London,Department of Informatics,London,UK

Publisher

IEEE

Cited by 29 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. LPR: Large Language Models-Aided Program Reduction;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

2. Towards standarized benchmarks of LLMs in software modeling tasks: a conceptual framework;Software and Systems Modeling;2024-09-03

3. Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap;ACM Transactions on Autonomous and Adaptive Systems;2024-08-20

4. Esale: Enhancing Code-Summary Alignment Learning for Source Code Summarization;IEEE Transactions on Software Engineering;2024-08

5. Adopting automated bug assignment in practice — a longitudinal case study at Ericsson;Empirical Software Engineering;2024-07-30
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