An Empirical Comparison of Machine Learning Techniques in Predicting the Bug Severity of Open and Closed Source Projects

Publisher： IGI Global_journal

E-ISSN： 1942-3934|4|2|32-59

ISSN： 1942-3926

Source： International Journal of Open Source Software and Processes (IJOSSP), Vol.4, Iss.2, 2012-04, pp. : 32-59

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

From Android Bug Reports to Android Bug Handling Process: An Empirical Study of Open-Source Development

By  

International Journal of Open Source Software and Processes (IJOSSP), Vol. 7, Iss. 4, 2016-10 ,pp. : 1-18

IGI Global_journal

Access to resources Recommend Favorite

Two Level Empirical Study of Logging Statements in Open Source Java Projects

By  

International Journal of Open Source Software and Processes (IJOSSP), Vol. 6, Iss. 1, 2015-01 ,pp. : 49-73

IGI Global_journal

Access to resources Recommend Favorite

An Empirical Analysis of Software Changes on Statement Entity in Java Open Source Projects

By  

International Journal of Open Source Software and Processes (IJOSSP), Vol. 4, Iss. 2, 2012-04 ,pp. : 16-31

IGI Global_journal

Access to resources Recommend Favorite

PREDICTING STUDENTS' PERFORMANCE IN DISTANCE LEARNING USING MACHINE LEARNING TECHNIQUES

By KOTSIANTIS S.  

Applied Artificial Intelligence, Vol. 18, Iss. 5, 2004-05 ,pp. : 411-426

Taylor & Francis Ltd

Access to resources Recommend Favorite

The Effects of Communication Patterns on the Success of Open Source Software Projects: An Empirical Analysis from Social Network Perspectives

By  

Journal of Global Information Management (JGIM), Vol. 24, Iss. 4, 2016-10 ,pp. : 22-44

IGI Global_journal

Access to resources Recommend Favorite