Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques

KHAN, Zanis Ali; SHIN, Donghwan; BIANCULLI, Domenico; BRIAND, Lionel

doi:10.1145/3510003.3510101

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Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques

KHAN, Zanis Ali; SHIN, Donghwan; BIANCULLI, Domenico et al.

2022 • In Proceedings of the 44th International Conference on Software Engineering (ICSE ’22)

Peer reviewed

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https://hdl.handle.net/10993/50072

DOI
10.1145/3510003.3510101

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Keywords :

logs; template identification; metrics

Abstract :

[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.

Research center :

Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab)

Disciplines :

Computer science

Author, co-author :

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

External co-authors :

Language :

English

Title :

Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques

Publication date :

July 2022

Event name :

44th International Conference on Software Engineering (ICSE ’22)

Event date :

from 21-05-2022 to 29-05-2022

Audience :

International

Main work title :

Proceedings of the 44th International Conference on Software Engineering (ICSE ’22)

Publisher :

ACM, New York, NY, United States

Pages :

1095-1106

Peer reviewed :

Peer reviewed

Focus Area :

Security, Reliability and Trust

Commentary :

The paper presentation can be found here: https://youtu.be/R_bEdohzn6M

Available on ORBilu :

since 27 January 2022

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