Log analysis is crucial in software maintenance, prompting the need for summarizing and monitoring logs over time. The authors introduce a semantic-based clustering method to track defects efficiently. By collaborating with Software Reliability Engineers, they develop criteria for successful log evolution monitoring. Their algorithm dynamically updates log clusters based on semantic representations and introduces a novel evaluation metric. Experiments show superior performance compared to traditional methods across industrial and public datasets.
To Another Language
from source content
arxiv.org
Key Insights Distilled From
by Rares Dolga,... at arxiv.org 03-14-2024
https://arxiv.org/pdf/2403.08358.pdfDeeper Inquiries