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Authors: Gözde Koçak ; Burak Turhan and Ayşe Bener

Affiliation: Boğaziçi University, Turkey

ISBN: 978-989-8111-52-4

Keyword(s): Software testing, Defect Prediction, Call Graph, Empirical Analysis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Case-Based Reasoning ; Enterprise Information Systems ; Enterprise Software Technologies ; Pattern Recognition ; Software Economics ; Software Engineering ; Symbolic Systems ; Theory and Methods

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 several formats:
Koçak G.; Turhan B.; Bener A. and (2008). PREDICTING DEFECTS IN A LARGE TELECOMMUNICATION SYSTEM.In Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT, ISBN 978-989-8111-52-4, pages 284-288. DOI: 10.5220/0001887502840288

@conference{icsoft08,
author={Gözde Ko\c{C}ak 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 3: ICSOFT,},
year={2008},
pages={284-288},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001887502840288},
isbn={978-989-8111-52-4},
}

TY - CONF

JO - Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: 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

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