@conference {Hata:2008:EFF:1370750.1370772,
	title = {An extension of fault-prone filtering using precise training and a dynamic threshold},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	pages = {89{\textendash}98},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Fault-prone module detection in source code is important for assurance of software quality. Most previous fault-prone detection approaches have been based on software metrics. Such approaches, however, have difficulties in collecting the metrics and in constructing mathematical models based on the metrics. To mitigate such difficulties, we have proposed a novel approach for detecting fault-prone modules using a spam-filtering technique, named Fault-Prone Filtering. In our approach, fault-prone modules are detected in such a way that the source code modules are considered as text files and are applied to the spam filter directly. In practice, we use the training only errors procedure and apply this procedure to fault-prone. Since no pre-training is required, this procedure can be applied to an actual development field immediately. This paper describes an extension of the training only errors procedures. We introduce a precise unit of training, "modified lines of code," instead of methods. In addition, we introduce the dynamic threshold for classification. The result of the experiment shows that our extension leads to twice the precision with about the same recall, and improves 15\% on the best F1 measurement.},
	keywords = {eclipse, fault-prone modules, spam filter, text mining},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370772},
	url = {http://doi.acm.org/10.1145/1370750.1370772},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p89-hata.pdf},
	author = {Hata, Hideaki and Mizuno, Osamu and Kikuno, Tohru}
}
@article {102,
	title = {Empirical validation of object-oriented metrics on open source software for fault prediction},
	journal = {IEEE Transactions on Software Engineering},
	volume = {31},
	number = {10},
	year = {2005},
	note = {"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."
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},
	pages = {897-910},
	abstract = {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.},
	keywords = {bugs, bugzilla, cbo, defects, dit, fault-prone modules, faults, lcom, lcomn, loc, metrics, mozilla, noc, object-oriented, rfc, source code, wmc},
	url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.115.8372\&rep=rep1\&type=pdf},
	attachments = {https://flosshub.org/sites/flosshub.org/files/Gyimothy.pdf},
	author = {Gyimothy, T. and Ferenc, R. and Siket, I.}
}
