<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gyimothy, T.</style></author><author><style face="normal" font="default" size="100%">Ferenc, R.</style></author><author><style face="normal" font="default" size="100%">Siket, I.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Empirical validation of object-oriented metrics on open source software for fault prediction</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Software Engineering</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">bugs</style></keyword><keyword><style  face="normal" font="default" size="100%">bugzilla</style></keyword><keyword><style  face="normal" font="default" size="100%">cbo</style></keyword><keyword><style  face="normal" font="default" size="100%">defects</style></keyword><keyword><style  face="normal" font="default" size="100%">dit</style></keyword><keyword><style  face="normal" font="default" size="100%">fault-prone modules</style></keyword><keyword><style  face="normal" font="default" size="100%">faults</style></keyword><keyword><style  face="normal" font="default" size="100%">lcom</style></keyword><keyword><style  face="normal" font="default" size="100%">lcomn</style></keyword><keyword><style  face="normal" font="default" size="100%">loc</style></keyword><keyword><style  face="normal" font="default" size="100%">metrics</style></keyword><keyword><style  face="normal" font="default" size="100%">mozilla</style></keyword><keyword><style  face="normal" font="default" size="100%">noc</style></keyword><keyword><style  face="normal" font="default" size="100%">object-oriented</style></keyword><keyword><style  face="normal" font="default" size="100%">rfc</style></keyword><keyword><style  face="normal" font="default" size="100%">source code</style></keyword><keyword><style  face="normal" font="default" size="100%">wmc</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.115.8372&amp;rep=rep1&amp;type=pdf</style></url></web-urls><related-urls><url><style face="normal" font="default" size="100%">http://flosshub.org/sites/flosshub.org/files/Gyimothy.pdf</style></url></related-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">897-910</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Open source software systems are becoming increasingly important these days. Many companies are investing in open source projects and lots of them are also using such software in their own work. But, because open source software is often developed with a different management style than the industrial ones, the quality and reliability of the code needs to be studied. Hence, the characteristics of the source code of these projects need to be measured to obtain more information about it. This paper describes how we calculated the object-oriented metrics given by Chidamber and Kemerer to illustrate how fault-proneness detection of the source code of the open source Web and e-mail suite called Mozilla can be carried out. We checked the values obtained against the number of bugs found in its bug database - called Bugzilla - using regression and machine learning methods to validate the usefulness of these metrics for fault-proneness prediction. We also compared the metrics of several versions of Mozilla to see how the predicted fault-proneness of the software system changed during its development cycle.</style></abstract><accession-num><style face="normal" font="default" size="100%">WOS:000233015300008</style></accession-num><notes><style face="normal" font="default" size="100%">&quot;This paper describes how we calculated the object-oriented metrics given by Chidamber and Kemerer to illustrate how fault-proneness detection of the source code of the open source Web and e-mail suite called Mozilla can be carried out. We checked the values obtained against the number of bugs found in its bug database - called Bugzilla - using regression and machine learning methods to validate the usefulness of these metrics for fault-proneness prediction. We also compared the metrics of several versions of Mozilla to see how the predicted fault-proneness of the software system changed during its development cycle.&quot;
metrics, 
wmc weighted methods per class, 
dit depth of inheritance, 
rfc response for a class,
noc number of children,
cbo coupling between object classes,
cohesion,
lines of code, loc, sloc
chidamber and kemerer metrics</style></notes><custom1><style face="normal" font="default" size="100%">software engineering</style></custom1><custom2><style face="normal" font="default" size="100%">case study</style></custom2></record></records></xml>
