Fetching the paper…
Reading the bibliography…
Log parsing, the process of converting raw log messages into structured formats, is an important initial step for automated analysis of logs of large-scale software systems.
Uniparser: A unified log parser for heterogeneous log data. In Proceedings of the ACM Web Conference 2022 . 1893–1901
Yudong Liu, Xu Zhang, Shilin He, Hongyu Zhang, Liqun Li, Yu Kang, Yong Xu, Minghua Ma, Qingwei Lin, Yingnong Dang, et al · 1901
Earlier work this paper cites.
Term-weighting approaches in automatic text retrieval
Gerard Salton and Christopher Buckley. 1988 · 1988
Earlier work this paper cites.
Computation of normalized edit distance and applications
Andres Marzal and Enrique Vidal. 1993 · 1993
Earlier work this paper cites.
A density-based algorithm for discovering clusters in large spatial databases with noise. In kdd , Vol. 96. 226–231
Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu, et al · 1996
Earlier work this paper cites.
Abstracting execution logs to execution events for enterprise applications (short paper). In 2008 The Eighth International Conference on Quality Software . IEEE, 181–186
Zhen Ming Jiang, Ahmed E Hassan, Parminder Flora, and Gilbert Hamann. 2008 · 2008
Earlier work this paper cites.
Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics
Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, and Michael R. Lyu. 2023 · 2008
Earlier work this paper cites.
Execution anomaly detection in distributed systems through unstructured log analysis. In 2009 ninth IEEE international conference on data mining . IEEE, 149–158
Qiang Fu, Jian-Guang Lou, Yi Wang, and Jiang Li. 2009 · 2009
Earlier work this paper cites.
Clustering event logs using iterative partitioning. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining . 1255–1264
Adetokunbo AO Makanju, A Nur Zincir-Heywood, and Evangelos E Milios. 2009 · 2009
Earlier work this paper cites.
Efficiently extracting operational profiles from execution logs using suffix arrays. In 2009 20th International Symposium on Software Reliability Engineering . IEEE, 41–50
Meiyappan Nagappan, Kesheng Wu, and Mladen A Vouk. 2009 · 2009
Earlier work this paper cites.
Detecting large-scale system problems by mining console logs. In Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles . 117–132
Wei Xu, Ling Huang, Armando Fox, David Patterson, and Michael I Jordan. 2009 · 2009
Earlier work this paper cites.
Abstracting log lines to log event types for mining software system logs. In 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010) . IEEE, 114–117
Meiyappan Nagappan and Mladen A Vouk. 2010 · 2010
Earlier work this paper cites.
Scikit-learn: Machine learning in Python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al · 2011
Earlier work this paper cites.
LogSig: Generating system events from raw textual logs. In Proceedings of the 20th ACM international conference on Information and knowledge management . 785–794
Liang Tang, Tao Li, and Chang-Shing Perng. 2011 · 2011
Earlier work this paper cites.
Determinantal point processes for machine learning
Alex Kulesza, Ben Taskar, et al · 2012
Earlier work this paper cites.
Toward fine-grained, unsupervised, scalable performance diagnosis for production cloud computing systems
Haibo Mi, Huaimin Wang, Yangfan Zhou, Michael Rung-Tsong Lyu, and Hua Cai. 2013 · 2013
Earlier work this paper cites.
Detection of early-stage enterprise infection by mining large-scale log data. In 2015 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks . IEEE, 45–56
Alina Oprea, Zhou Li, Ting-Fang Yen, Sang H Chin, and Sumayah Alrwais. 2015 · 2015
Earlier work this paper cites.
Logcluster-a data clustering and pattern mining algorithm for event logs. In 2015 11th International conference on network and service management (CNSM) . IEEE, 1–7
Risto Vaarandi and Mauno Pihelgas. 2015 · 2015
Earlier work this paper cites.
Spell: Streaming parsing of system event logs. In 2016 IEEE 16th International Conference on Data Mining (ICDM) . IEEE, 859–864
Min Du and Feifei Li. 2016 · 2016
Earlier work this paper cites.
Length matters: Clustering system log messages using length of words
Keiichi Shima. 2016 · 2016
Cited alongside, same era.
Drain: An online log parsing approach with fixed depth tree. In 2017 IEEE International Conference on Web Services (ICWS) . IEEE, 33–40
Pinjia He, Jieming Zhu, Zibin Zheng, and Michael R Lyu. 2017 · 2017
Cited alongside, same era.
Logsed: Anomaly diagnosis through mining time-weighted control flow graph in logs. In 2017 IEEE 10th International Conference on Cloud Computing (CLOUD) . IEEE, 447–455
Tong Jia, Lin Yang, Pengfei Chen, Ying Li, Fanjing Meng, and Jingmin Xu. 2017 · 2017
Cited alongside, same era.
DBSCAN revisited, revisited: why and how you should (still) use DBSCAN
Erich Schubert, Jörg Sander, Martin Ester, Hans Peter Kriegel, and Xiaowei Xu. 2017 · 2017
Cited alongside, same era.
Examining the stability of logging statements
Suhas Kabinna, Cor-Paul Bezemer, Weiyi Shang, Mark D Syer, and Ahmed E Hassan. 2018 · 2018
A large collection of system log datasets for AI-powered log analytics
2023 · 2023
Later among the works it cites.
Batch Prompting: Efficient Inference with Large Language Model APIs. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track . 792–810
Zhoujun Cheng, Jungo Kasai, and Tao Yu. 2023 · 2023
Later among the works it cites.
From images to textual prompts: Zero-shot visual question answering with frozen large language models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 10867–10877
Jiaxian Guo, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Boyang Li, Dacheng Tao, and Steven Hoi. 2023 · 2023
Later among the works it cites.
Decomposed Prompting: A Modular Approach for Solving Complex Tasks. In The Eleventh International Conference on Learning Representations
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, and Ashish Sabharwal. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) . 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Poirot: Aligning attack behavior with kernel audit records for cyber threat hunting. In Proceedings of the 2019 ACM SIGSAC conference on computer and communications security . 1795–1812
Sadegh M Milajerdi, Birhanu Eshete, Rigel Gjomemo, and VN Venkatakrishnan. 2019 · 2019
Cited alongside, same era.
Robust log-based anomaly detection on unstable log data. In Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering . 807–817
Xu Zhang, Yong Xu, Qingwei Lin, Bo Qiao, Hongyu Zhang, Yingnong Dang, Chunyu Xie, Xinsheng Yang, Qian Cheng, Ze Li, et al · 2019
Cited alongside, same era.
Tools and benchmarks for automated log parsing. In 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) . IEEE, 121–130
Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, and Michael R Lyu. 2019 · 2019
Cited alongside, same era.
Logram: Efficient log parsing using n-gram dictionaries
Hetong Dai, Heng Li, Che Shao Chen, Weiyi Shang, and Tse-Hsun Chen. 2020 · 2020
Cited alongside, same era.
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . 7871–7880
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
Self-attentive classification-based anomaly detection in unstructured logs. In 2020 IEEE International Conference on Data Mining (ICDM) . IEEE, 1196–1201
Sasho Nedelkoski, Jasmin Bogatinovski, Alexander Acker, Jorge Cardoso, and Odej Kao. 2020 · 2020
Cited alongside, same era.
Log Parsing: How Far Can ChatGPT Go?. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 1699–1704
Van-Hoang Le and Hongyu Zhang. 2023a · 2023
Later among the works it cites.
Log parsing with prompt-based few-shot learning. In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 2438–2449
Van-Hoang Le and Hongyu Zhang. 2023b · 2023
Later among the works it cites.
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023 · 2023
Later among the works it cites.
OpenAI. 2023 · 2023
Later among the works it cites.
Log parsing evaluation in the era of modern software systems. In 2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE) . IEEE, 379–390
Stefan Petrescu, Floris Den Hengst, Alexandru Uta, and Jan S Rellermeyer. 2023 · 2023
Later among the works it cites.
Prompting large language models with answer heuristics for knowledge-based visual question answering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 14974–14983
Zhenwei Shao, Zhou Yu, Meng Wang, and Jun Yu. 2023 · 2023
Later among the works it cites.
Brain: Log parsing with bidirectional parallel tree
Siyu Yu, Pinjia He, Ningjiang Chen, and Yifan Wu. 2023 · 2023
Later among the works it cites.
OpenAI ChatGPT
2024 · 2024
Closest in time.
CigaR: Cost-efficient Program Repair with LLMs
Dávid Hidvégi, Khashayar Etemadi, Sofia Bobadilla, and Martin Monperrus. 2024 · 2024
Closest in time.
Logshrink: Effective log compression by leveraging commonality and variability of log data. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering . 1–12
Xiaoyun Li, Hongyu Zhang, Van-Hoang Le, and Pengfei Chen. 2024 · 2024
Closest in time.
LLMParser: An Exploratory Study on Using Large Language Models for Log Parsing. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering (ICSE ’24) . ACM
Zeyang Ma, An Ran Chen, Dong Jae Kim, Tse-Hsun Chen, and Shaowei Wang. 2024 · 2024
Closest in time.
Fuzz4all: Universal fuzzing with large language models. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering . 1–13
Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, and Lingming Zhang. 2024 · 2024
Closest in time.
DivLog: Log Parsing with Prompt Enhanced In-Context Learning. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering . 1–12
Junjielong Xu, Ruichun Yang, Yintong Huo, Chengyu Zhang, and Pinjia He. 2024 · 2024
Closest in time.
Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging
Wei Zhang, Hongcheng Guo, Anjie Le, Jian Yang, Jiaheng Liu, Zhoujun Li, Tieqiao Zheng, Shi Xu, Runqiang Zang, Liangfan Zheng, and Bo Zhang. 2024 · 2024
Closest in time.