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Generalizing fault contents from a few classes
Madrid, Spain September 20-September 21
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ESEM.2007.39First International Symposium on Empi ...
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Hanna Scott, Philip M. Johnson, "Generalizing fault contents from a few classes," Empirical Software Engineering and Measurement, International Symposium on, pp. 205-214, First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007), 2007.
 
 
BibTex
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@article{ 10.1109/ESEM.2007.39,
author = {Hanna Scott and Philip M. Johnson},
title = {Generalizing fault contents from a few classes},
journal ={Empirical Software Engineering and Measurement, International Symposium on},
volume = {0},
year = {2007},
issn = {1938-6451},
pages = {205-214},
doi = {http://doi.ieeecomputersociety.org/10.1109/ESEM.2007.39},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Empirical Software Engineering and Measurement, International Symposium on
TI - Generalizing fault contents from a few classes
SN - 1938-6451
SP205
EP214
A1 - Hanna Scott,
A1 - Philip M. Johnson,
PY - 2007
KW - null
VL - 0
JA - Empirical Software Engineering and Measurement, International Symposium on
ER -
 
Hanna Scott, Blekinge Institute of Technology, Sweden
Philip M. Johnson, University of Hawaii, USA
The challenges in fault prediction today are to get a prediction as early as possible, at as low a cost as possible, needing as little data as possible and preferably in such a language that your average developer can understand where it came from.

This paper presents a fault sampling method where a summary of a few, easily available metrics is used together with the results of a few sampled classes to generalize the fault content to an entire system. The method is tested on a large software system written in Java, that currently consists of around 2 000 classes and 300 000 lines of code. The evaluation shows that the fault generalization method is good at predicting fault-prone clusters and that it is possible to generalize the values of a few representative classes.

Citation:
Hanna Scott, Philip M. Johnson, "Generalizing fault contents from a few classes," esem, pp.205-214, First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007), 2007
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