Event clustering for log reduction and run time system understanding

Authors:
Kostas Kontogiannis;Ahmed Wasfy;Serge Mankovskii
Affiliations:
National Technical Univ. of Athens;Univ. of Waterloo;CA Labs, CA Technologies, Markham ON
Venue:
Proceedings of the 2011 ACM Symposium on Applied Computing
Year:
2011

Citing 2
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A framework for dynamic program analyzers

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A heuristic search approach to solving the software clustering problem

A heuristic search approach to solving the software clustering problem

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Abstract

Large software systems are constantly monitored so that audits can be initiated, once a failure occurs or when maintenance operations are performed. However, the log files are usually sizeable, and require filtering and reduction in order to be processed efficiently. In this paper, we define the concept of the Event Dependency Graph, and we discuss an event filtering and a use case identification technique, that is based on event clustering. This technique can be used to reduce the size of system logs and assist on system analysis and, program understanding.