A Bayesian Belief Network for Modeling Open Source Software Maintenance Productivity

TitleA Bayesian Belief Network for Modeling Open Source Software Maintenance Productivity
Publication TypeBook Chapter
Year of Publication2016
AuthorsBibi, Stamatia, Ampatzoglou Apostolos, and Stamelos Ioannis
Secondary AuthorsCrowston, Kevin, Hammouda Imed, Lundell Björn, Robles Gregorio, Gamalielsson Jonas, and Lindman Juho
Secondary TitleOpen Source Systems: Integrating Communities: 12th IFIP WG 2.13 International Conference, OSS 2016, Gothenburg, Sweden, May 30 - June 2, 2016, Proceedings
ChapterA Bayesian Belief Network for Modeling Open Source Software Maintenance Productivity
Pagination32–44
PublisherSpringer International Publishing
Place PublishedCham
ISBN Number978-3-319-39225-7
Abstract

Maintenance is one of the most effort consuming activities in the software development lifecycle. Efficient maintenance within short release cycles depends highly on the underlying source code structure, in the sense that complex modules are more difficult to maintain. In this paper we attempt to unveil and discuss relationships between maintenance productivity, the structural quality of the source code and process metrics like the type of a release and the number of downloads. To achieve this goal, we developed a Bayesian Belief Network (BBN) involving several maintainability predictors and three managerial indices for maintenance (i.e., duration, production, and productivity) on 20 open source software projects. The results suggest that maintenance duration depends on inheritance, coupling, and process metrics. On the other hand maintenance production and productivity depend mostly on code quality metrics.

URLhttp://dx.doi.org/10.1007/978-3-319-39225-7_3
DOI10.1007/978-3-319-39225-7_3