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Abstract
Logging is a common practice in software engineering to provide insights into working systems. The main uses of log files have always been failure identification and root cause analysis. In recent years, novel applications of logging have emerged that benefit from automated analysis of log files, for example, real-time monitoring of system health, understanding users’ behavior, and extracting domain knowledge. Although nearly every software system produces log files, the biggest challenge in log analysis is the lack of a common standard for both the content and format of log data. This paper provides a systematic review of recent literature (covering the period between 2000 and June 2021, concentrating primarily on the last five years of this period) related to automated log analysis. Our contribution is three-fold: we present an overview of various research areas in the field; we identify different types of log files that are used in research, and we systematize the content of log files. We believe that this paper serves as a valuable starting point for new researchers in the field, as well as an interesting overview for those looking for other ways of utilizing log information.
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Authors (2)
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Łukasz Korzeniowski mgr inż.
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Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/ACCESS.2022.3152549
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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IEEE Access
no. 10,
pages 21892 - 21913,
ISSN: 2169-3536 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Korzeniowski Ł., Goczyła K.: Landscape of Automated Log Analysis: A Systematic Literature Review and Mapping Study// IEEE Access -Vol. 10, (2022), s.21892-21913
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/access.2022.3152549
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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