How Webmining and Coupling Metrics Improve Early Program Comprehension

Authors:
Andy Zaidman;Bart Du Bois;Serge Demeyer
Affiliations:
University of Antwerp, Belgium;University of Antwerp, Belgium;University of Antwerp, Belgium
Venue:
ICPC '06 Proceedings of the 14th IEEE International Conference on Program Comprehension
Year:
2006

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Abstract

During initial program comprehension, software engineers could benefit from knowing the most need-to-beunderstood classes in the system under study in order to kick-start their software reconnaissance. Previously we have used webmining techniques on runtime trace data to identify these important classes. Here, we reprise this webmining technique and make a thorough comparison of its effectiveness when collecting static information of the software system under study. Apache Ant and Jakarta JMeter, two medium-scale open source Java software systems, serve as case studies. From publicly available developers notes we conclude that the webmining technique in combination with dynamic analysis provides the best results with a level of recall of 90% when comparing with the developers' opinion.