Abstract
Much effort has been devoted to the development and empirical
validation of object-oriented metrics. The empirical validations
performed thus far would suggest that a core set of validated metrics is
close to being identified. However, none of these studies allow for the
potentially confounding effect of class size. We demonstrate a strong
size confounding effect and question the results of previous
object-oriented metrics validation studies. We first investigated
whether there is a confounding effect of class size in validation
studies of object-oriented metrics and show that, based on previous
work, there is reason to believe that such an effect exists. We then
describe a detailed empirical methodology for identifying those effects.
Finally, we perform a study on a large C++ telecommunications framework
to examine if size is really a confounder. This study considered the
Chidamber and Kemerer metrics and a subset of the Lorenz and Kidd
metrics. The dependent variable was the incidence of a fault
attributable to a field failure (fault-proneness of a class). Our
findings indicate that, before controlling for size, the results are
very similar to previous studies. The metrics that are expected to be
validated are indeed associated with fault-proneness
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