Event clustering for log reduction and run time system understanding

Kontogiannis, K; Wasfy, A; Mankovskii, S

dc.contributor.author	Kontogiannis, K	en
dc.contributor.author	Wasfy, A	en
dc.contributor.author	Mankovskii, S	en
dc.date.accessioned	2014-03-01T02:53:16Z
dc.date.available	2014-03-01T02:53:16Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36203
dc.subject	clustering	en
dc.subject	log analysis	en
dc.subject	log reduction	en
dc.subject	software systems	en
dc.subject	use case determination	en
dc.subject.other	clustering	en
dc.subject.other	Log analysis	en
dc.subject.other	Log reductions	en
dc.subject.other	software systems	en
dc.subject.other	use case determination	en
dc.subject.other	Computer software	en
dc.subject.other	Systems analysis	en
dc.subject.other	Computer software maintenance	en
dc.title	Event clustering for log reduction and run time system understanding	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1982185.1982229	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1982185.1982229	en
heal.publicationDate	2011	en
heal.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. © 2011 Authors.	en
heal.journalName	Proceedings of the ACM Symposium on Applied Computing	en
dc.identifier.doi	10.1145/1982185.1982229	en
dc.identifier.spage	191	en
dc.identifier.epage	192	en