Publication Details

EvoParser: An Evolutionary Approach to Log Parsing

SETINSKÝ Jiří and ŽÁDNÍK Martin. EvoParser: An Evolutionary Approach to Log Parsing. In: 38th IEEE/IFIP Network Operations and Management Symposium (NOMS 2025). Honolulu: IEEE Communications Society, 2025, p. 8.
Type
conference paper
Language
english
Authors
Abstract

In the domain of network operations and manage-
ment, efficient log parsing is crucial for processing the high
volumes of log data necessary to monitor the reliability and
performance of the operated infrastructures and services. This
paper introduces a novel method for creating highly efficient
log parsers. Our method employs a genetic algorithm to evolve
optimized log parsing graphs that deliver high-quality parsing
results. Experimental evaluations demonstrate that our approach achieves results comparable to or better than state-of-the-art techniques while maintaining low complexity during parsing.
These characteristics make it particularly suitable for real-time
applications in high-volume data scenarios.

Published
2025 (in print)
Pages
8
Proceedings
38th IEEE/IFIP Network Operations and Management Symposium (NOMS 2025)
Conference
IEEE/IFIP Network Operations and Management Symposium 2025, Honolulu, US
Publisher
IEEE Communications Society
Place
Honolulu, US
BibTeX
@INPROCEEDINGS{FITPUB13271,
   author = "Ji\v{r}\'{i} Setinsk\'{y} and Martin \v{Z}\'{a}dn\'{i}k",
   title = "EvoParser: An Evolutionary Approach to Log Parsing",
   pages = 8,
   booktitle = "38th IEEE/IFIP Network Operations and Management Symposium (NOMS 2025)",
   year = 2025,
   location = "Honolulu, US",
   publisher = "IEEE Communications Society",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/13271"
}
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