{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T05:23:02Z","timestamp":1776489782229,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,4,20]],"date-time":"2024-04-20T00:00:00Z","timestamp":1713571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Research Grants Council of the Hong Kong Special Administrative Region, China","award":["14206921"],"award-info":[{"award-number":["14206921"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,4,20]]},"DOI":"10.1145\/3643795.3648392","type":"proceedings-article","created":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T13:46:19Z","timestamp":1725975979000},"page":"70-74","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Enhancing LLM-Based Coding Tools through Native Integration of IDE-Derived Static Context"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8370-644X","authenticated-orcid":false,"given":"Yichen","family":"Li","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1936-5598","authenticated-orcid":false,"given":"Yun","family":"Peng","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8798-5667","authenticated-orcid":false,"given":"Yintong","family":"Huo","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3666-5798","authenticated-orcid":false,"given":"Michael R.","family":"Lyu","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Hong Kong, China"}]}],"member":"320","published-online":{"date-parts":[[2024,9,10]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"DeepSeek AI. 2023. DeepSeek Coder: Let the Code Write Itself. https:\/\/github.com\/deepseek-ai\/DeepSeek-Coder."},{"key":"e_1_3_2_1_2_1","unstructured":"Amazon. 2023. CodeWhisperer. https:\/\/aws.amazon.com\/cn\/codewhisperer\/"},{"key":"e_1_3_2_1_3_1","unstructured":"Ramakrishna Bairi Atharv Sonwane Aditya Kanade Arun Iyer Suresh Parthasarathy Sriram Rajamani B Ashok Shashank Shet et al. 2023. Code-Plan: Repository-level Coding using LLMs and Planning. arXiv preprint arXiv:2309.12499 (2023)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3540250.3549162"},{"key":"e_1_3_2_1_5_1","unstructured":"CodeGeeX. 2023. CodeGeeX. https:\/\/models.aminer.cn\/codegeex\/blog\/"},{"key":"e_1_3_2_1_6_1","volume-title":"Hantian Ding, Ming Tan, Nihal Jain, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, et al.","author":"Ding Yangruibo","year":"2023","unstructured":"Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad, Hantian Ding, Ming Tan, Nihal Jain, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, et al. 2023. CROSSCODEEVAL: A Diverse and Multilingual Benchmark for Cross-File Code Completion. arXiv preprint arXiv:2310.11248 (2023)."},{"key":"e_1_3_2_1_7_1","volume-title":"Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, and Bing Xiang.","author":"Ding Yangruibo","year":"2022","unstructured":"Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, and Bing Xiang. 2022. Cocomic: Code completion by jointly modeling in-file and cross-file context. arXiv preprint arXiv:2212.10007 (2022)."},{"key":"e_1_3_2_1_8_1","volume-title":"LoGenText-Plus: Improving Neural Machine Translation-based Logging Texts Generation with Syntactic Templates. ACM Transactions on Software Engineering and Methodology","author":"Ding Zishuo","year":"2023","unstructured":"Zishuo Ding, Yiming Tang, Xiaoyu Cheng, Heng Li, and Weiyi Shang. 2023. LoGenText-Plus: Improving Neural Machine Translation-based Logging Texts Generation with Syntactic Templates. ACM Transactions on Software Engineering and Methodology (2023)."},{"key":"e_1_3_2_1_9_1","volume-title":"Constructing Effective In-Context Demonstration for Code Intelligence Tasks: An Empirical Study. arXiv preprint arXiv:2304.07575","author":"Gao Shuzheng","year":"2023","unstructured":"Shuzheng Gao, Xin-Cheng Wen, Cuiyun Gao, Wenxuan Wang, and Michael R Lyu. 2023. Constructing Effective In-Context Demonstration for Code Intelligence Tasks: An Empirical Study. arXiv preprint arXiv:2304.07575 (2023)."},{"key":"e_1_3_2_1_10_1","unstructured":"GitHub. 2023. GitHub Copilot: Your AI pair programmer. https:\/\/github.com\/features\/copilot"},{"key":"e_1_3_2_1_11_1","volume-title":"Do not give away my secrets: Uncovering the privacy issue of neural code completion tools. arXiv preprint arXiv:2309.07639","author":"Huang Yizhan","year":"2023","unstructured":"Yizhan Huang, Yichen Li, Weibin Wu, Jianping Zhang, and Michael R Lyu. 2023. Do not give away my secrets: Uncovering the privacy issue of neural code completion tools. arXiv preprint arXiv:2309.07639 (2023)."},{"key":"e_1_3_2_1_12_1","unstructured":"JetBrains. 2023. idea. https:\/\/www.jetbrains.com\/help\/idea\/code-inspection.html"},{"key":"e_1_3_2_1_13_1","first-page":"9459","article-title":"2020. Retrieval-augmented generation for knowledge-intensive nlp tasks","volume":"33","author":"Lewis Patrick","year":"2020","unstructured":"Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Kuttler, Mike Lewis, Wen-tau Yih, Tim Rockt\u00e4schel, et al. 2020. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in Neural Information Processing Systems 33 (2020), 9459--9474.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_14_1","volume-title":"Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, et al.","author":"Li Raymond","year":"2023","unstructured":"Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, et al. 2023. StarCoder: may the source be with you! arXiv preprint arXiv:2305.06161 (2023)."},{"key":"e_1_3_2_1_15_1","volume-title":"Reacc: A retrieval-augmented code completion framework. arXiv preprint arXiv:2203.07722","author":"Lu Shuai","year":"2022","unstructured":"Shuai Lu, Nan Duan, Hojae Han, Daya Guo, Seung-won Hwang, and Alexey Svyatkovskiy. 2022. Reacc: A retrieval-augmented code completion framework. arXiv preprint arXiv:2203.07722 (2022)."},{"key":"e_1_3_2_1_16_1","unstructured":"Microsoft. 2023. Pylance. https:\/\/marketplace.visualstudio.com\/items?itemName=ms-python.vscode-pylance"},{"key":"e_1_3_2_1_17_1","unstructured":"Microsoft. 2023. vscode. https:\/\/code.visualstudio.com"},{"key":"e_1_3_2_1_18_1","unstructured":"NumPy. 2023. numpy. https:\/\/numpy.org"},{"key":"e_1_3_2_1_19_1","unstructured":"OpenAI. 2021. CodeX. https:\/\/openai.com\/blog\/openai-codex"},{"key":"e_1_3_2_1_20_1","unstructured":"OpenAI. 2023. ChatGPT. https:\/\/openai.com\/blog\/chatgpt\/"},{"key":"e_1_3_2_1_21_1","volume-title":"Generative Type Inference for Python. arXiv preprint arXiv:2307.09163","author":"Peng Yun","year":"2023","unstructured":"Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, and Michael R Lyu. 2023. Generative Type Inference for Python. arXiv preprint arXiv:2307.09163 (2023)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TOOLS.2000.891358"},{"key":"e_1_3_2_1_23_1","volume-title":"Codebleu: a method for automatic evaluation of code synthesis. arXiv preprint arXiv:2009.10297","author":"Ren Shuo","year":"2020","unstructured":"Shuo Ren, Daya Guo, Shuai Lu, Long Zhou, Shujie Liu, Duyu Tang, Neel Sundaresan, Ming Zhou, Ambrosio Blanco, and Shuai Ma. 2020. Codebleu: a method for automatic evaluation of code synthesis. arXiv preprint arXiv:2009.10297 (2020)."},{"key":"e_1_3_2_1_24_1","volume-title":"RepoFusion: Training Code Models to Understand Your Repository. arXiv preprint arXiv:2306.10998","author":"Shrivastava Disha","year":"2023","unstructured":"Disha Shrivastava, Denis Kocetkov, Harm de Vries, Dzmitry Bahdanau, and Torsten Scholak. 2023. RepoFusion: Training Code Models to Understand Your Repository. arXiv preprint arXiv:2306.10998 (2023)."},{"key":"e_1_3_2_1_25_1","volume-title":"Chunqiu Steven Xia, and Lingming Zhang","author":"Wei Yuxiang","year":"2023","unstructured":"Yuxiang Wei, Chunqiu Steven Xia, and Lingming Zhang. 2023. Copiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair. arXiv preprint arXiv:2309.00608 (2023)."},{"key":"e_1_3_2_1_26_1","volume-title":"Conversational automated program repair. arXiv preprint arXiv:2301.13246","author":"Xia Chunqiu Steven","year":"2023","unstructured":"Chunqiu Steven Xia and Lingming Zhang. 2023. Conversational automated program repair. arXiv preprint arXiv:2301.13246 (2023)."},{"key":"e_1_3_2_1_27_1","volume-title":"Private-library-oriented code generation with large language models. arXiv preprint arXiv:2307.15370","author":"Zan Daoguang","year":"2023","unstructured":"Daoguang Zan, Bei Chen, Yongshun Gong, Junzhi Cao, Fengji Zhang, Bingchao Wu, Bei Guan, Yilong Yin, and Yongji Wang. 2023. Private-library-oriented code generation with large language models. arXiv preprint arXiv:2307.15370 (2023)."},{"key":"e_1_3_2_1_28_1","volume-title":"Repocoder: Repository-level code completion through iterative retrieval and generation. arXiv preprint arXiv:2303.12570","author":"Zhang Fengji","year":"2023","unstructured":"Fengji Zhang, Bei Chen, Yue Zhang, Jin Liu, Daoguang Zan, Yi Mao, Jian-Guang Lou, and Weizhu Chen. 2023. Repocoder: Repository-level code completion through iterative retrieval and generation. arXiv preprint arXiv:2303.12570 (2023)."}],"event":{"name":"LLM4Code '24: 1st International Workshop on Large Language Models for Code","location":"Lisbon Portugal","acronym":"LLM4Code '24","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering","IEEE CS","Faculty of Engineering of University of Porto"]},"container-title":["Proceedings of the 1st International Workshop on Large Language Models for Code"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3643795.3648392","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3643795.3648392","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:57:45Z","timestamp":1750294665000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3643795.3648392"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,20]]},"references-count":28,"alternative-id":["10.1145\/3643795.3648392","10.1145\/3643795"],"URL":"https:\/\/doi.org\/10.1145\/3643795.3648392","relation":{},"subject":[],"published":{"date-parts":[[2024,4,20]]},"assertion":[{"value":"2024-09-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}