Using a class abstraction technique to predict faults in OO classes: a case study through six releases of the Eclipse JDT

Authors:
Djuradj Babich;Peter J. Clarke;James F. Power;B. M. Golam Kibria
Affiliations:
Florida International University, Miami;Florida International University, Miami;National University of Ireland, Maynooth, Kildare;Florida International University, Miami
Venue:
Proceedings of the 2011 ACM Symposium on Applied Computing
Year:
2011

Citing 13
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Abstract

In this paper, we propose an innovative suite of metrics based on a class abstraction that uses a taxonomy for OO classes (CAT) to capture aspects of software complexity through combinations of class characteristics. We empirically validate their ability to predict fault prone classes using fault data for six versions of the Java-based open-source Eclipse Integrated Development Environment. We conclude that this proposed CAT metric suite, even though it treats classes in groups rather than individually, is as effective as the traditional Chidamber and Kemerer metrics in identifying fault-prone classes.