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Permanent link (DOI): https://doi.org/10.7939/R3497V

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Theses and Dissertations

Using Citation Influence and Social Network Analysis to Predict Software Defects Open Access

Descriptions

Other title
Subject/Keyword
social network analysis
citation influence
software defects
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Hu, Wei
Supervisor and department
Wong, Kenny (Computing Science)
Examining committee member and department
Stroulia, Eleni (Computing Science)
Barbosa, Denilson (Computing Science)
Greiner, Russell (Computing Science)
Wong, Kenny (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2013-07-03T13:31:43Z
Graduation date
2013-11
Degree
Master of Science
Degree level
Master's
Abstract
Resource constraints, e.g. lack of time and human resources, is a major issue in software testing practice. In short, testers have limited time to test software systems. Therefore, managers are expected to spend more resources on software components that are likely to contain many defects. To help managers make better decisions of selective testing, it is beneficial to identify defect-prone software components before the actual testing. In this thesis, we propose a model for software defect prediction. The proposed model combines the topological properties of the software dependency network and the textual information in source code to predict defect-prone software components. We evaluate our model on data from Eclipse, Netbeans, and Gnome projects at different levels of granularity. The evaluation results are encouraging, showing that our model achieves higher prediction accuracy than prior work.
Language
English
DOI
doi:10.7939/R3497V
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Wei Hu and Kenny Wong: Using citation influences to predict software defects. In Proceedings of the 10th Working Conference on Mining Software Repository, MSR ’13, pages 419-428, Piscataway, NJ, USA, 2013. IEEE Press.

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