Managing Trace Data Volume through a Heuristical Clustering Process Based on Event Execution Frequency

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Eighth Euromicro Working Conference on Software Maintenance and Reengineering (CSMR'04)

Tampere, Finland

March 24-March 26

ISBN: 0-7695-2107-X

	ASCII Text	x
	Andy Zaidman, Serge Demeyer, "Managing Trace Data Volume through a Heuristical Clustering Process Based on Event Execution Frequency," Software Maintenance and Reengineering, European Conference on, pp. 329, Eighth Euromicro Working Conference on Software Maintenance and Reengineering (CSMR'04), 2004.

	BibTex	x
	@article{ 10.1109/CSMR.2004.1281435, author = {Andy Zaidman and Serge Demeyer}, title = {Managing Trace Data Volume through a Heuristical Clustering Process Based on Event Execution Frequency}, journal ={Software Maintenance and Reengineering, European Conference on}, volume = {0}, year = {2004}, issn = {1534-5351}, pages = {329}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSMR.2004.1281435}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Software Maintenance and Reengineering, European Conference on TI - Managing Trace Data Volume through a Heuristical Clustering Process Based on Event Execution Frequency SN - 1534-5351 SP EP A1 - Andy Zaidman, A1 - Serge Demeyer, PY - 2004 KW - null VL - 0 JA - Software Maintenance and Reengineering, European Conference on ER -

Andy Zaidman, University of Antwerp, Belgium

Serge Demeyer, University of Antwerp, Belgium

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSMR.2004.1281435

To regain architectural insight into a program using dynamic analysis, one of the major stumbling blocks remains the large amount of trace data collected. Therefore, this paper proposes a heuristic which divides the trace data into recurring event clusters. To compose such clusters the Euclidian distance is used as a dissimilarity measure on the frequencies of the events. Manual inspection of these event sequences revealed that the heuristic provides interesting starting points for further examination.

Citation:

Andy Zaidman, Serge Demeyer, "Managing Trace Data Volume through a Heuristical Clustering Process Based on Event Execution Frequency," csmr, pp.329, Eighth Euromicro Working Conference on Software Maintenance and Reengineering (CSMR'04), 2004

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