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A Survey on Automated Log Analysis for Reliability Engineering
arXiv - CS - Software Engineering Pub Date : 2020-09-15 , DOI: arxiv-2009.07237 Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, Michael R. Lyu
arXiv - CS - Software Engineering Pub Date : 2020-09-15 , DOI: arxiv-2009.07237 Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, Michael R. Lyu
Logs are semi-structured text generated by logging statements in software
source code. In recent decades, software logs have become imperative in the
reliability assurance mechanism of many software systems because they are often
the only data available that record software runtime information. As modern
software is evolving into a large scale, the volume of logs has increased
rapidly. To enable effective and efficient usage of modern software logs in
reliability engineering, a number of studies have been conducted on automated
log analysis. This survey presents a detailed overview of automated log
analysis research, including how to automate and assist the writing of logging
statements, how to compress logs, how to parse logs into structured event
templates, and how to employ logs to detect anomalies, predict failures, and
facilitate diagnosis. Additionally, we survey work that releases open-source
toolkits and datasets. Based on the discussion of the recent advances, we
present several promising future directions toward real-world and
next-generation automated log analysis.
中文翻译:
可靠性工程自动化日志分析综述
日志是由软件源代码中的日志语句生成的半结构化文本。近几十年来,软件日志在许多软件系统的可靠性保证机制中变得必不可少,因为它们通常是记录软件运行时信息的唯一可用数据。随着现代软件向大规模演进,日志量迅速增加。为了在可靠性工程中有效和高效地使用现代软件日志,已经对自动日志分析进行了大量研究。本次调查详细介绍了自动化日志分析研究,包括如何自动化和辅助编写日志语句、如何压缩日志、如何将日志解析为结构化的事件模板,以及如何利用日志来检测异常、预测故障、并方便诊断。此外,我们还调查了发布开源工具包和数据集的工作。基于对最新进展的讨论,我们提出了几个有希望的未来方向,即现实世界和下一代自动日志分析。
更新日期:2020-09-16
中文翻译:
可靠性工程自动化日志分析综述
日志是由软件源代码中的日志语句生成的半结构化文本。近几十年来,软件日志在许多软件系统的可靠性保证机制中变得必不可少,因为它们通常是记录软件运行时信息的唯一可用数据。随着现代软件向大规模演进,日志量迅速增加。为了在可靠性工程中有效和高效地使用现代软件日志,已经对自动日志分析进行了大量研究。本次调查详细介绍了自动化日志分析研究,包括如何自动化和辅助编写日志语句、如何压缩日志、如何将日志解析为结构化的事件模板,以及如何利用日志来检测异常、预测故障、并方便诊断。此外,我们还调查了发布开源工具包和数据集的工作。基于对最新进展的讨论,我们提出了几个有希望的未来方向,即现实世界和下一代自动日志分析。