@inproceedings{zhu-etal-2024-survey-natural,
title = "A Survey on Natural Language Processing for Programming",
author = "Zhu, Qingfu and
Luo, Xianzhen and
Liu, Fang and
Gao, Cuiyun and
Che, Wanxiang",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.149",
pages = "1690--1704",
abstract = "Natural language processing for programming aims to use NLP techniques to assist programming. It is increasingly prevalent for its effectiveness in improving productivity. Distinct from natural language, a programming language is highly structured and functional. Constructing a structure-based representation and a functionality-oriented algorithm is at the heart of program understanding and generation. In this paper, we conduct a systematic review covering tasks, datasets, evaluation methods, techniques, and models from the perspective of the structure-based and functionality-oriented property, aiming to understand the role of the two properties in each component. Based on the analysis, we illustrate unexplored areas and suggest potential directions for future work.",
}
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%0 Conference Proceedings
%T A Survey on Natural Language Processing for Programming
%A Zhu, Qingfu
%A Luo, Xianzhen
%A Liu, Fang
%A Gao, Cuiyun
%A Che, Wanxiang
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F zhu-etal-2024-survey-natural
%X Natural language processing for programming aims to use NLP techniques to assist programming. It is increasingly prevalent for its effectiveness in improving productivity. Distinct from natural language, a programming language is highly structured and functional. Constructing a structure-based representation and a functionality-oriented algorithm is at the heart of program understanding and generation. In this paper, we conduct a systematic review covering tasks, datasets, evaluation methods, techniques, and models from the perspective of the structure-based and functionality-oriented property, aiming to understand the role of the two properties in each component. Based on the analysis, we illustrate unexplored areas and suggest potential directions for future work.
%U https://aclanthology.org/2024.lrec-main.149
%P 1690-1704
Markdown (Informal)
[A Survey on Natural Language Processing for Programming](https://aclanthology.org/2024.lrec-main.149) (Zhu et al., LREC-COLING 2024)
ACL
- Qingfu Zhu, Xianzhen Luo, Fang Liu, Cuiyun Gao, and Wanxiang Che. 2024. A Survey on Natural Language Processing for Programming. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 1690–1704, Torino, Italia. ELRA and ICCL.