This is the repository of our paper: A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond.
Please do not hesitate to contact us or launch pull requests if you find any related papers that are missing in our paper.
- Update on 2024/06/23: Version 1.2 released 🚀
- Update on 2024/03/19: Version 1.0 released 🚀
- Update on 2024/01/19: Add multiple reading lists 📖
- Update on 2023/12/29: Add Development Timelines 📅
- Update on 2023/12/25: Add Reading Lists, Merry Christmas 🍎🎄
📃 A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond
Qiushi Sun, Zhirui Chen, Fangzhi Xu, Kanzhi Cheng, Chang Ma, Zhangyue Yin, Jianing Wang, Chengcheng Han, Renyu Zhu, Shuai Yuan, Qipeng Guo, Xipeng Qiu, Pengcheng Yin, Xiaoli Li, Fei Yuan, Lingpeng Kong, Xiang Li, Zhiyong Wu
Introducing the resources provided by our survey paper.
The Development of Code Intelligence
- Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models 2024.06
- Symbolic Learning Enables Self-Evolving Agents 2024.06
- aiXcoder 2024.04
- Making Language Models Better Tool Learners with Execution Feedback 2024.03
- Language Models for Code 🤖
- Evaluations and Benchmarks 📊
- Code Repair 🔧
- Reasoning with Code Synthesis 🧠
- Data Science 🔢
- Corpus containing Code Data 📚
- Code-Based Solutions for NLP Tasks 📝
- Code Empowered Agents 🤖
- Reinforcement Learning with CodeLMs 🎮
- Code Intelligence assists AI4Science 🧪
- Software Development 🛠️
- Multilingual 🌍
- Multimodal Code Generation 🎨
- Awesome Slides, Talks and Blogs 🧑🏫
🫶 If you are interested in our work or find this repository helpful, please consider using the following citation format when referencing our paper:
@article{sun2024survey,
title={A survey of neural code intelligence: Paradigms, advances and beyond},
author={Sun, Qiushi and Chen, Zhirui and Xu, Fangzhi and Cheng, Kanzhi and Ma, Chang and Yin, Zhangyue and Wang, Jianing and Han, Chengcheng and Zhu, Renyu and Yuan, Shuai and others},
journal={arXiv preprint arXiv:2403.14734},
year={2024}
}This is an open collaborative research project among:
