Publication Details
EvoParser: An Evolutionary Approach to Log Parsing
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.
@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" }