{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T16:00:29Z","timestamp":1785340829171,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":48,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T00:00:00Z","timestamp":1775952000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Research Grants Council of the Hong Kong Special Administrative Region, China","award":["CUHK 14209124, and SRFS2425-4S03"],"award-info":[{"award-number":["CUHK 14209124, and SRFS2425-4S03"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,12]]},"DOI":"10.1145\/3794763.3794796","type":"proceedings-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T15:18:58Z","timestamp":1785338338000},"page":"26-37","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["AutoLogger: A Multi-Agent Framework for the End-to-End Automated Logging"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6626-4437","authenticated-orcid":false,"given":"Renyi","family":"Zhong","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8798-5667","authenticated-orcid":false,"given":"Yintong","family":"Huo","sequence":"additional","affiliation":[{"name":"Singapore Management University, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1096-2732","authenticated-orcid":false,"given":"Wenwei","family":"Gu","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8370-644X","authenticated-orcid":false,"given":"Yichen","family":"Li","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"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, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,29]]},"reference":[{"key":"e_1_3_3_1_2_2","unstructured":"Anonymous Authers. 2025. The replication package of AutoLogger. https:\/\/anonymous.4open.science\/r\/AutoLogger-F0D2\/"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE55347.2025.00157"},{"key":"e_1_3_3_1_4_2","unstructured":"Thanh-Long Bui Hoa\u00a0Khanh Dam and Rashina Hoda. 2025. An LLM-based multi-agent framework for agile effort estimation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2509.14483 (2025)."},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2017.15"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/SANER53432.2022.00051"},{"key":"e_1_3_3_1_7_2","unstructured":"Google. 2024. google-java-format. https:\/\/github.com\/google\/google-java-format"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"crossref","unstructured":"Junda He Christoph Treude and David Lo. 2025. LLM-Based Multi-Agent Systems for Software Engineering: Literature Review Vision and the Road Ahead. ACM Transactions on Software Engineering and Methodology 34 5 (2025) 1\u201330.","DOI":"10.1145\/3712003"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Shilin He Pinjia He Zhuangbin Chen Tianyi Yang Yuxin Su and Michael\u00a0R Lyu. 2021. A survey on automated log analysis for reliability engineering. ACM computing surveys (CSUR) 54 6 (2021) 1\u201337.","DOI":"10.1145\/3460345"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3540250.3558963"},{"key":"e_1_3_3_1_11_2","unstructured":"Edward\u00a0J Hu Yelong Shen Phillip Wallis Zeyuan Allen-Zhu Yuanzhi Li Shean Wang Lu Wang Weizhu Chen et\u00a0al. 2022. Lora: Low-rank adaptation of large language models. ICLR 1 2 (2022) 3."},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/SANER.2016.29"},{"key":"e_1_3_3_1_13_2","unstructured":"Diederik\u00a0P. Kingma and Jimmy Ba. 2017. Adam: A Method for Stochastic Optimization. arxiv:https:\/\/arXiv.org\/abs\/1412.6980\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/1412.6980"},{"key":"e_1_3_3_1_14_2","unstructured":"Andy Lawrence and Lenny Simon. 2023. Annual Outage Analysis 2023. https:\/\/uptimeinstitute.com\/resources\/research-and-reports\/annual-outage-analysis-2023 Accessed: 2025-09-30."},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","unstructured":"Yichen Li Yintong Huo Zhihan Jiang Renyi Zhong Pinjia He Yuxin Su Lionel\u00a0C. Briand and Michael\u00a0R. Lyu. 2024. Exploring the Effectiveness of LLMs in Automated Logging Statement Generation: An Empirical Study. IEEE Transactions on Software Engineering (TSE) 50 12 (2024) 3188\u20133207. 10.1109\/TSE.2024.3475375","DOI":"10.1109\/TSE.2024.3475375"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Yichen Li Yintong Huo Renyi Zhong Zhihan Jiang Jinyang Liu Junjie Huang Jiazhen Gu Pinjia He and Michael\u00a0R Lyu. 2024. Go static: Contextualized logging statement generation. Proceedings of the ACM on Software Engineering (FSE) 1 FSE (2024) 609\u2013630.","DOI":"10.1145\/3643754"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/3324884.3416636"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE43902.2021.00131"},{"key":"e_1_3_3_1_19_2","first-page":"74","volume-title":"Text summarization branches out","author":"Lin Chin-Yew","year":"2004","unstructured":"Chin-Yew Lin. 2004. Rouge: A package for automatic evaluation of summaries. In Text summarization branches out. 74\u201381."},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3533767.3534379"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","unstructured":"Zhongxin Liu Xin Xia David Lo Zhenchang Xing Ahmed\u00a0E. Hassan and Shanping Li. 2019. Which Variables Should I Log? IEEE Transactions on Software Engineering (TSE) (2019) 1\u20131. 10.1109\/TSE.2019.2941943","DOI":"10.1109\/TSE.2019.2941943"},{"key":"e_1_3_3_1_22_2","first-page":"330","volume-title":"2025 IEEE\/ACM 47th International Conference on Software Engineering (ICSE)","author":"Ma Wei","year":"2024","unstructured":"Wei Ma, Daoyuan Wu, Yuqiang Sun, Tianwen Wang, Shangqing Liu, Jian Zhang, Yue Xue, and Yang Liu. 2024. Combining Fine-tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications. In 2025 IEEE\/ACM 47th International Conference on Software Engineering (ICSE). IEEE Computer Society, 330\u2013342."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"Antonio Mastropaolo Valentina Ferrari Luca Pascarella and Gabriele Bavota. 2024. Log statements generation via deep learning: Widening the support provided to developers. Journal of Systems and Software (JSS) 210 (2024) 111947.","DOI":"10.1016\/j.jss.2023.111947"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3511561"},{"key":"e_1_3_3_1_25_2","unstructured":"Modal Labs Inc.2024. Modal. https:\/\/modal.com\/."},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-4380-9_12"},{"key":"e_1_3_3_1_27_2","unstructured":"OpenObserve. 2024. Enterprise Observability Strategy: Key Insights for 2024. OpenObserve Blog. https:\/\/openobserve.ai\/blog\/enterprise-observability-strategy-insights\/ Accessed: 2025-09-30."},{"key":"e_1_3_3_1_28_2","first-page":"311","volume-title":"Proceedings of the 40th annual meeting of the Association for Computational Linguistics (ACL)","author":"Papineni Kishore","year":"2002","unstructured":"Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics (ACL). 311\u2013318."},{"key":"e_1_3_3_1_29_2","unstructured":"Riley Peronto. 2024. Four steps to reduce log data costs: A practical guide. https:\/\/chronosphere.io\/learn\/steps-to-reduce-log-data-costs\/ Accessed: 2025-09-30."},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.acl-long.810"},{"key":"e_1_3_3_1_31_2","unstructured":"Md\u00a0Nakhla Rafi Dong\u00a0Jae Kim Tse-Hsun Chen and Shaowei Wang. 2024. A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2409.13642 (2024)."},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"crossref","unstructured":"Stephen Robertson Hugo Zaragoza et\u00a0al. 2009. The probabilistic relevance framework: BM25 and beyond. Foundations and Trends\u00ae in Information Retrieval 3 4 (2009) 333\u2013389.","DOI":"10.1561\/1500000019"},{"key":"e_1_3_3_1_33_2","unstructured":"Puneet Saraswat. 2020. Cloud Logging Optimization - How We Saved Over $140k in Logging Costs. Harness (2020). https:\/\/www.harness.io\/blog\/cloud-logging-optimization Accessed: 2025-09-30."},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2502.03160"},{"key":"e_1_3_3_1_35_2","doi-asserted-by":"crossref","unstructured":"Wei Tao Yucheng Zhou Yanlin Wang Wenqiang Zhang Hongyu Zhang and Yu Cheng. 2024. Magis: Llm-based multi-agent framework for github issue resolution. Advances in Neural Information Processing Systems 37 (2024) 51963\u201351993.","DOI":"10.52202\/079017-1647"},{"key":"e_1_3_3_1_36_2","unstructured":"The Apache Software Foundation. 2025. Apache Doris. https:\/\/github.com\/apache\/doris."},{"key":"e_1_3_3_1_37_2","unstructured":"The Apache Software Foundation. 2025. Apache Kafka. https:\/\/github.com\/apache\/kafka."},{"key":"e_1_3_3_1_38_2","unstructured":"The Apache Software Foundation. 2025. Apache ZooKeeper. https:\/\/github.com\/apache\/zookeeper."},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"crossref","unstructured":"Ruiqi Wang Jiyu Guo Cuiyun Gao Guodong Fan Chun\u00a0Yong Chong and Xin Xia. 2025. Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2502.06193 (2025).","DOI":"10.1145\/3728963"},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"publisher","DOI":"10.1145\/3650212.3652107"},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1145\/3597503.3623326"},{"key":"e_1_3_3_1_42_2","volume-title":"The eleventh international conference on learning representations","author":"Yao Shunyu","unstructured":"Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik\u00a0R Narasimhan, and Yuan Cao. [n. d.]. React: Synergizing reasoning and acting in language models. In The eleventh international conference on learning representations."},{"key":"e_1_3_3_1_43_2","first-page":"293","volume-title":"10th USENIX Symposium on Operating Systems Design and Implementation (OSDI 12)","author":"Yuan Ding","year":"2012","unstructured":"Ding Yuan, Soyeon Park, Peng Huang, Yang Liu, Michael\u00a0M Lee, Xiaoming Tang, Yuanyuan Zhou, and Stefan Savage. 2012. Be Conservative: Enhancing Failure Diagnosis with Proactive Logging. In 10th USENIX Symposium on Operating Systems Design and Implementation (OSDI 12). 293\u2013306."},{"key":"e_1_3_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2012.6227202"},{"key":"e_1_3_3_1_45_2","doi-asserted-by":"publisher","unstructured":"Yuhao Zeng Jinfu Chen Weiyi Shang et\u00a0al. 2019. Studying the characteristics of logging practices in mobile apps: a case study on F-Droid. Empirical Software Engineering (EMSE) 24 (2019) 3394\u20133434. 10.1007\/s10664-019-09687-9","DOI":"10.1007\/s10664-019-09687-9"},{"key":"e_1_3_3_1_46_2","doi-asserted-by":"publisher","DOI":"10.1145\/3132747.3132778"},{"key":"e_1_3_3_1_47_2","doi-asserted-by":"publisher","unstructured":"Renyi Zhong Yichen Li Jinxi Kuang Wenwei Gu Yintong Huo and Michael\u00a0R. Lyu. 2025. LogUpdater: Automated Detection and Repair of Specific Defects in Logging Statements. ACM Trans. Softw. Eng. Methodol. (TOSEM) (April 2025). 10.1145\/3731754Just Accepted.","DOI":"10.1145\/3731754"},{"key":"e_1_3_3_1_48_2","unstructured":"Renyi Zhong Yichen Li Guangba Yu Wenwei Gu Jinxi Kuang Yintong Huo and Michael\u00a0R Lyu. 2025. Larger Is Not Always Better: Exploring Small Open-source Language Models in Logging Statement Generation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2505.16590 (2025)."},{"key":"e_1_3_3_1_49_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2015.60"}],"event":{"name":"ICPC '26: 34th IEEE\/ACM International Conference on Program Comprehension","location":"Rio de Janeiro , Brazil","acronym":"ICPC '26","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering"]},"container-title":["Proceedings of the 2026 34th IEEE\/ACM International Conference on Program Comprehension"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3794763.3794796","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T15:20:16Z","timestamp":1785338416000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3794763.3794796"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":48,"alternative-id":["10.1145\/3794763.3794796","10.1145\/3794763"],"URL":"https:\/\/doi.org\/10.1145\/3794763.3794796","relation":{},"subject":[],"published":{"date-parts":[[2026,4,12]]},"assertion":[{"value":"2026-07-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}