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ICSE2022Top-tier venue

Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques

Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand

2022Year
77Citations
17Top-tier citations

Abstract

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.

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