{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T05:30:30Z","timestamp":1775885430274,"version":"3.50.1"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,6,3]],"date-time":"2025-06-03T00:00:00Z","timestamp":1748908800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,3]],"date-time":"2025-06-03T00:00:00Z","timestamp":1748908800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100000038","name":"the Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","award":["RGPIN-2021-03900"],"award-info":[{"award-number":["RGPIN-2021-03900"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100000038","name":"the Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","award":["RGPIN-2021-03900"],"award-info":[{"award-number":["RGPIN-2021-03900"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100000038","name":"the Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","award":["RGPIN-2021-03900"],"award-info":[{"award-number":["RGPIN-2021-03900"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Fonds de recherche du Qu\u00e9bec\u2013 Nature et technologies","award":["326866"],"award-info":[{"award-number":["326866"]}]},{"name":"the Fonds de recherche du Qu\u00e9bec\u2013 Nature et technologies","award":["326866"],"award-info":[{"award-number":["326866"]}]},{"name":"the Fonds de recherche du Qu\u00e9bec\u2013 Nature et technologies","award":["326866"],"award-info":[{"award-number":["326866"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Autom Softw Eng"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1007\/s10515-025-00527-3","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T23:12:45Z","timestamp":1748905965000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["What information contributes to log-based anomaly detection? Insights from a configurable transformer-based approach"],"prefix":"10.1007","volume":"32","author":[{"given":"Xingfang","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Foutse","family":"Khomh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,3]]},"reference":[{"key":"527_CR1","doi-asserted-by":"crossref","unstructured":"Bodik, P., Goldszmidt, M., Fox, A., Woodard, D.B., Andersen, H.: Fingerprinting the datacenter: automated classification of performance crises. In: Proceedings of the 5th European Conference on Computer Systems, pp. 111\u2013124 (2010)","DOI":"10.1145\/1755913.1755926"},{"key":"527_CR2","doi-asserted-by":"crossref","unstructured":"Chen, M., Zheng, A.X., Lloyd, J., Jordan, M.I., Brewer, E.: Failure diagnosis using decision trees. In: International Conference on Autonomic Computing, 2004. Proceedings., pp. 36\u201343 (2004). IEEE","DOI":"10.1109\/ICAC.2004.1301345"},{"key":"527_CR3","unstructured":"Chen, Z., Liu, J., Gu, W., Su, Y., Lyu, M.R.: Experience report: Deep learning-based system log analysis for anomaly detection. arXiv:2107.05908 (2021)"},{"key":"527_CR4","unstructured":"Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805 (2018)"},{"key":"527_CR5","doi-asserted-by":"crossref","unstructured":"Du, M., Li, F., Zheng, G., Srikumar, V.: Deeplog: Anomaly detection and diagnosis from system logs through deep learning. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 1285\u20131298 (2017)","DOI":"10.1145\/3133956.3134015"},{"key":"527_CR6","unstructured":"Hugging Face: all-MiniLM-L6-v2 Model. https:\/\/huggingface.co\/sentence-transformers\/all-MiniLM-L6-v2. Accessed 8 Apr 2024"},{"issue":"3","key":"527_CR7","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1016\/j.icte.2020.06.003","volume":"6","author":"A Farzad","year":"2020","unstructured":"Farzad, A., Gulliver, T.A.: Unsupervised log message anomaly detection. ICT Express 6(3), 229\u2013237 (2020)","journal-title":"ICT Express"},{"key":"527_CR8","doi-asserted-by":"crossref","unstructured":"Guo, H., Yuan, S., Wu, X.: Logbert: Log anomaly detection via bert. In: 2021 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138 (2021). IEEE","DOI":"10.1109\/IJCNN52387.2021.9534113"},{"key":"527_CR9","doi-asserted-by":"crossref","unstructured":"Guo, H., Yang, J., Liu, J., Bai, J., Wang, B., Li, Z., Zheng, T., Zhang, B., Peng, J., Tian, Q.: Logformer: A pre-train and tuning pipeline for log anomaly detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, pp. 135\u2013143 (2024)","DOI":"10.1609\/aaai.v38i1.27764"},{"key":"527_CR10","doi-asserted-by":"crossref","unstructured":"Haviv, A., Ram, O., Press, O., Izsak, P., Levy, O.: Transformer language models without positional encodings still learn positional information. In: Goldberg, Y., Kozareva, Z., Zhang, Y. (eds.) Findings of the Association for Computational Linguistics: EMNLP 2022, pp. 1382\u20131390. Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (2022). https:\/\/aclanthology.org\/2022.findings-emnlp.99","DOI":"10.18653\/v1\/2022.findings-emnlp.99"},{"key":"527_CR11","doi-asserted-by":"crossref","unstructured":"He, S., Zhu, J., He, P., Lyu, M.R.: Experience report: System log analysis for anomaly detection. In: 2016 IEEE 27th International Symposium on Software Reliability Engineering (ISSRE), pp. 207\u2013218 (2016). IEEE","DOI":"10.1109\/ISSRE.2016.21"},{"key":"527_CR12","doi-asserted-by":"crossref","unstructured":"He, P., Zhu, J., Zheng, Z., Lyu, M.R.: Drain: An online log parsing approach with fixed depth tree. In: 2017 IEEE International Conference on Web Services (ICWS), pp. 33\u201340 (2017). IEEE","DOI":"10.1109\/ICWS.2017.13"},{"key":"527_CR13","doi-asserted-by":"crossref","unstructured":"He, S., Lin, Q., Lou, J.-G., Zhang, H., Lyu, M.R., Zhang, D.: Identifying impactful service system problems via log analysis. In: Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 60\u201370 (2018)","DOI":"10.1145\/3236024.3236083"},{"issue":"6","key":"527_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3460345","volume":"54","author":"S He","year":"2021","unstructured":"He, S., He, P., Chen, Z., Yang, T., Su, Y., Lyu, M.R.: A survey on automated log analysis for reliability engineering. ACM Comput. Surv. (CSUR) 54(6), 1\u201337 (2021)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"527_CR15","doi-asserted-by":"crossref","unstructured":"Irie, K., Zeyer, A., Schl\u00fcter, R., Ney, H.: Language modeling with deep transformers. arXiv:1905.04226 (2019)","DOI":"10.21437\/Interspeech.2019-2225"},{"key":"527_CR16","unstructured":"Kazemi, S.M., Goel, R., Eghbali, S., Ramanan, J., Sahota, J., Thakur, S., Wu, S., Smyth, C., Poupart, P., Brubaker, M.: Time2vec: Learning a vector representation of time. arXiv:1907.05321 (2019)"},{"key":"527_CR17","doi-asserted-by":"crossref","unstructured":"Landauer, M., Skopik, F., Wurzenberger, M.: A critical review of common log data sets used for evaluation of sequence-based anomaly detection techniques. Proc. ACM Softw. Eng. 1(FSE), 1354\u20131375 (2024)","DOI":"10.1145\/3660768"},{"key":"527_CR18","doi-asserted-by":"crossref","unstructured":"Le, V.-H., Zhang, H.: Log-based anomaly detection without log parsing. In: 2021 36th IEEE\/ACM International Conference on Automated Software Engineering (ASE), pp. 492\u2013504 (2021). IEEE","DOI":"10.1109\/ASE51524.2021.9678773"},{"key":"527_CR19","doi-asserted-by":"crossref","unstructured":"Le, V.-H., Zhang, H.: Log-based anomaly detection with deep learning: how far are we? In: 2022 IEEE\/ACM 44th International Conference on Software Engineering (ICSE), pp. 1356\u20131367 (2022). IEEE","DOI":"10.1145\/3510003.3510155"},{"key":"527_CR20","doi-asserted-by":"crossref","unstructured":"Li, X., Chen, P., Jing, L., He, Z., Yu, G.: Swisslog: Robust and unified deep learning based log anomaly detection for diverse faults. In: 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE), pp. 92\u2013103 (2020). IEEE","DOI":"10.1109\/ISSRE5003.2020.00018"},{"key":"527_CR21","doi-asserted-by":"crossref","unstructured":"Liang, Y., Zhang, Y., Xiong, H., Sahoo, R.: Failure prediction in ibm bluegene\/l event logs. In: Seventh IEEE International Conference on Data Mining (ICDM 2007), pp. 583\u2013588 (2007). IEEE","DOI":"10.1109\/ICDM.2007.46"},{"key":"527_CR22","doi-asserted-by":"crossref","unstructured":"Lin, Q., Zhang, H., Lou, J.-G., Zhang, Y., Chen, X.: Log clustering based problem identification for online service systems. In: Proceedings of the 38th International Conference on Software Engineering Companion, pp. 102\u2013111 (2016)","DOI":"10.1145\/2889160.2889232"},{"key":"527_CR23","unstructured":"Lou, J.-G., Fu, Q., Yang, S., Xu, Y., Li, J.: Mining invariants from console logs for system problem detection. In: 2010 USENIX Annual Technical Conference (USENIX ATC 10) (2010)"},{"issue":"4","key":"527_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3447876","volume":"30","author":"Y Lyu","year":"2021","unstructured":"Lyu, Y., Li, H., Sayagh, M., Jiang, Z.M., Hassan, A.E.: An empirical study of the impact of data splitting decisions on the performance of aiops solutions. ACM Trans. Softw. Eng. Methodol. (TOSEM) 30(4), 1\u201338 (2021)","journal-title":"ACM Trans. Softw. Eng. Methodol. (TOSEM)"},{"key":"527_CR25","doi-asserted-by":"crossref","unstructured":"Nedelkoski, S., Bogatinovski, J., Acker, A., Cardoso, J., Kao, O.: Self-attentive classification-based anomaly detection in unstructured logs. In: 2020 IEEE International Conference on Data Mining (ICDM), pp. 1196\u20131201 (2020). IEEE","DOI":"10.1109\/ICDM50108.2020.00148"},{"key":"527_CR26","doi-asserted-by":"crossref","unstructured":"Oliner, A., Stearley, J.: What supercomputers say: A study of five system logs. In: 37th Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN\u201907), pp. 575\u2013584 (2007). IEEE","DOI":"10.1109\/DSN.2007.103"},{"issue":"2","key":"527_CR27","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1145\/2076450.2076466","volume":"55","author":"A Oliner","year":"2012","unstructured":"Oliner, A., Ganapathi, A., Xu, W.: Advances and challenges in log analysis. Commun. ACM 55(2), 55\u201361 (2012)","journal-title":"Commun. ACM"},{"key":"527_CR28","doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv:1908.10084 (2019)","DOI":"10.18653\/v1\/D19-1410"},{"key":"527_CR29","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Adv. Neural Inf. Process. Syst.\u00a030\u00a0(2017)"},{"key":"527_CR30","doi-asserted-by":"publisher","first-page":"124082","DOI":"10.1016\/j.eswa.2024.124082","volume":"251","author":"P Wang","year":"2024","unstructured":"Wang, P., Zhang, X., Cao, Z., Xu, W., Li, W.: Loggt: cross-system log anomaly detection via heterogeneous graph feature and transfer learning. Expert Syst. Appl. 251, 124082 (2024)","journal-title":"Expert Syst. Appl."},{"issue":"6","key":"527_CR31","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s10664-023-10364-1","volume":"28","author":"X Wu","year":"2023","unstructured":"Wu, X., Li, H., Khomh, F.: On the effectiveness of log representation for log-based anomaly detection. Empir. Softw. Eng. 28(6), 137 (2023)","journal-title":"Empir. Softw. Eng."},{"key":"527_CR32","doi-asserted-by":"crossref","unstructured":"Xu, W., Huang, L., Fox, A., Patterson, D., Jordan, M.I.: Detecting large-scale system problems by mining console logs. In: Proceedings of the ACM SIGOPS 22nd Symposium on Operating Systems Principles, pp. 117\u2013132 (2009)","DOI":"10.1145\/1629575.1629587"},{"key":"527_CR33","doi-asserted-by":"crossref","unstructured":"Yu, B., Yao, J., Fu, Q., Zhong, Z., Xie, H., Wu, Y., Ma, Y., He, P.: Deep learning or classical machine learning? an empirical study on log-based anomaly detection. In: Proceedings of the 46th IEEE\/ACM International Conference on Software Engineering, pp. 1\u201313 (2024)","DOI":"10.1145\/3597503.3623308"},{"key":"527_CR34","doi-asserted-by":"crossref","unstructured":"Zhang, X., Xu, Y., Lin, Q., Qiao, B., Zhang, H., Dang, Y., Xie, C., Yang, X., Cheng, Q., Li, Z., et al.: 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, pp. 807\u2013817 (2019)","DOI":"10.1145\/3338906.3338931"},{"key":"527_CR35","doi-asserted-by":"crossref","unstructured":"Zhu, J., He, S., Liu, J., He, P., Xie, Q., Zheng, Z., Lyu, M.R.: Tools and benchmarks for automated log parsing. In: 2019 IEEE\/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP), pp. 121\u2013130 (2019). IEEE","DOI":"10.1109\/ICSE-SEIP.2019.00021"},{"key":"527_CR36","doi-asserted-by":"crossref","unstructured":"Zhu, J., He, S., He, P., Liu, J., Lyu, M.R.: Loghub: A large collection of system log datasets for ai-driven log analytics. In: 2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE), pp. 355\u2013366 (2023). IEEE","DOI":"10.1109\/ISSRE59848.2023.00071"}],"container-title":["Automated Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10515-025-00527-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10515-025-00527-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10515-025-00527-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T13:56:39Z","timestamp":1757512599000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10515-025-00527-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,3]]},"references-count":36,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["527"],"URL":"https:\/\/doi.org\/10.1007\/s10515-025-00527-3","relation":{},"ISSN":["0928-8910","1573-7535"],"issn-type":[{"value":"0928-8910","type":"print"},{"value":"1573-7535","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,3]]},"assertion":[{"value":"30 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 June 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"58"}}