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The International Journal of Management Science and Information Technology (IJMSIT)

The international journal of management Science and information technology (IJMSIT) is a refereed journal and publishes high-quality theoretical and empirical papers in the areas of management science and information technology. This journal reports the impact of information technologies on the managerial and organizational topics. IJMSIT develops a comprehensive and theoretical framework by using a multidisciplinary approach to management and information technology for researchers and practitioners.

 


Editor-in-chief: J. J. Ferreira, University of Beira Interior, Portugal, Email: jjmf@ubi.pt
Published: Quarterly
Copyright: 2012, North American Institute of Science and Information Technology (NAISIT)
ISSN: ISSN 1923-0265 (Print) - ISSN 1923-0273 (Online) - ISSN 1923-0281 (CD-ROM)

AN EMPIRICAL PROCESS TO DERIVE OSS DEFECT ESTIMATION MODELS
1 : Issue 1 - (Jul-Sep 2011) ( 2011-07 )

Abstract:

Quality management in Open Source Software (OSS) has become a heated topic since the open source development model emerged. Much work has been done on exploring the distinct quality attributes in OSS, but very few studies covered quality estimation. In this paper, a general procedure is proposed to derive software quality estimation models for OSS projects and various candidate techniques are suggested for individual steps. The purpose is to build a model that estimates the number of defects in a project. Several statistical techniques and a machine learn­ing approach are used to examine the significance of quality predictors. Moreover, a neuro-fuzzy approach is adopted to improve accuracy of the estimation model. This procedure is followed and validated based on data from OSS projects.

Author(s): JIE XU - CANADA - UNIVERSITY OF WESTERN ONTARIO
LUIZ FERNANDO CAPRETZ - CANADA - UNIVERSITY OF WESTERN ONTARIO
DANNY HO - CANADA - UNIVERSITY OF WESTERN ONTARIO
Keywords: software quality, quality estimation, software metrics, regression, neurazl networks, fuzzy logic
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