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
Beschreibung
IEEE Xplore - The confounding effect of class size on the validity of object-oriented metrics
%0 Journal Article
%1 935855
%A Emam, Khaled El
%A Benlarbi, Saïda
%A Goel, Nishith
%A Rai, Shesh N.
%D 2001
%J IEEE Transactions on Software Engineering
%K Classes LOC Metrics OOP Objects Size
%N 7
%P 630--650
%R 10.1109/32.935855
%T The Confounding Effect of Class Size on the Validity of Object-Oriented Metrics
%V 27
%X 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
@article{935855,
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},
added-at = {2012-10-10T10:23:49.000+0200},
author = {Emam, Khaled El and Benlarbi, Saïda and Goel, Nishith and Rai, Shesh N.},
biburl = {https://www.bibsonomy.org/bibtex/2b917e2637675f96a0d936a3db8e18726/gron},
description = {IEEE Xplore - The confounding effect of class size on the validity of object-oriented metrics},
doi = {10.1109/32.935855},
interhash = {d7c528e530551d488eb5bd824510aea7},
intrahash = {b917e2637675f96a0d936a3db8e18726},
issn = {0098-5589},
journal = {IEEE Transactions on Software Engineering},
keywords = {Classes LOC Metrics OOP Objects Size},
month = {July},
number = 7,
pages = {630--650},
timestamp = {2013-07-29T22:06:54.000+0200},
title = {The Confounding Effect of Class Size on the Validity of Object-Oriented Metrics},
volume = 27,
year = 2001
}