[en] Log message template identification aims to convert raw logs
containing free-formed log messages into structured logs to be
processed by automated log-based analysis, such as anomaly detection
and model inference. While many techniques have been proposed in the
literature, only two recent studies provide a comprehensive evaluation
and comparison of the techniques using an established benchmark
composed of real-world logs. Nevertheless, we argue that both studies
have the following issues: (1) they used different accuracy metrics
without comparison between them, (2) some ground-truth (oracle)
templates are incorrect, and (3) the accuracy evaluation
results do not provide any information regarding incorrectly
identified templates.
In this paper, we address the above issues by providing three
guidelines for assessing the accuracy of log template identification
techniques: (1) use appropriate accuracy metrics, (2) perform oracle
template correction, and (3) perform analysis of incorrect templates. We then
assess the application of such guidelines through a comprehensive
evaluation of 14 existing template identification techniques on the
established benchmark logs. Results show very different insights than
existing studies and in particular a much less optimistic outlook on
existing techniques.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab)
Disciplines :
Sciences informatiques
Auteur, co-auteur :
KHAN, Zanis Ali ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
SHIN, Donghwan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
BIANCULLI, Domenico ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
BRIAND, Lionel ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques
Date de publication/diffusion :
juillet 2022
Nom de la manifestation :
44th International Conference on Software Engineering (ICSE ’22)
Date de la manifestation :
from 21-05-2022 to 29-05-2022
Manifestation à portée :
International
Titre de l'ouvrage principal :
Proceedings of the 44th International Conference on Software Engineering (ICSE ’22)
Maison d'édition :
ACM, New York, NY, Etats-Unis
Pagination :
1095-1106
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
Commentaire :
The paper presentation can be found here: https://youtu.be/R_bEdohzn6M
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