PREDICTING DEFECTS IN A LARGE TELECOMMUNICATION SYSTEM

Gözde Koçak, Burak Turhan, Ayşe Bener

Abstract

In a large software system knowing which files are most likely to be fault-prone is valuable information for project managers. However, our experience shows that it is difficult to collect and analyze fine-grained test defects in a large and complex software system. On the other hand, previous research has shown that companies can safely use cross company data with nearest neighbor sampling to predict their defects in case they are unable to collect local data. In this study we analyzed 25 projects of a large telecommunication system. To predict defect proneness of modules we learned from NASA MDP data. We used static call graph based ranking (CGBR) as well as nearest neighbor sampling for constructing method level defect predictors. Our results suggest that, for the analyzed projects, at least 70% of the defects can be detected by inspecting only i) 6% of the code using a Naïve Bayes model, ii) 3% of the code using CGBR framework.

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Paper Citation


in Harvard Style

Koçak G., Turhan B. and Bener A. (2008). PREDICTING DEFECTS IN A LARGE TELECOMMUNICATION SYSTEM . In Proceedings of the Third International Conference on Software and Data Technologies - Volume 2: ICSOFT, ISBN 978-989-8111-52-4, pages 284-288. DOI: 10.5220/0001887502840288


in Bibtex Style

@conference{icsoft08,
author={Gözde Koçak and Burak Turhan and Ayşe Bener},
title={PREDICTING DEFECTS IN A LARGE TELECOMMUNICATION SYSTEM},
booktitle={Proceedings of the Third International Conference on Software and Data Technologies - Volume 2: ICSOFT,},
year={2008},
pages={284-288},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001887502840288},
isbn={978-989-8111-52-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Software and Data Technologies - Volume 2: ICSOFT,
TI - PREDICTING DEFECTS IN A LARGE TELECOMMUNICATION SYSTEM
SN - 978-989-8111-52-4
AU - Koçak G.
AU - Turhan B.
AU - Bener A.
PY - 2008
SP - 284
EP - 288
DO - 10.5220/0001887502840288