Eighth Euromicro Working Conference on Software Maintenance and Reengineering (CSMR'04) Managing Trace Data Volume through a Heuristical Clustering Process Based on Event Execution Frequency Tampere, Finland March 24-March 26 ISBN: 0-7695-2107-X
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 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||