How Healthy Is My Project? Open Source Project Attributes as Indicators of Success

TitleHow Healthy Is My Project? Open Source Project Attributes as Indicators of Success
Publication TypeBook
Year of Publication2013
AuthorsPiggot, James, and Amrit Chintan
Secondary AuthorsPetrinja, Etiel, Succi Giancarlo, Ioini Nabil, and Sillitti Alberto
Secondary TitleIFIP Advances in Information and Communication Technology Open Source Software: Quality Verification
Pagination30 - 44
PublisherSpringer Berlin Heidelberg
Place PublishedBerlin, Heidelberg
ISSN Number1868-422X
ISBN Number978-3-642-38928-3
Keywordsflossmole, sourceforge

Determining what factors can influence the successful outcome of a software project has been labeled by many scholars and software engineers as a difficult problem. In this paper we use machine learning to create a model that can determine the stage a software project has obtained with some accuracy. Our model uses 8 Open Source project metrics to determine the stage a project is in. We validate our model using two performance measures; the exact success rate of classifying an Open Source Software project and the success rate over an interval of one stage of its actual performance using different scales of our dependent variable. In all cases we obtain an accuracy of above 70% with one away classification (a classification which is away by one) and about 40% accuracy with an exact classification. We also determine the factors (according to one classifier) that uses only eight variables among all the variables available in SourceForge, that determine the health of an OSS project.


"The dataset used has thus been obtained through a third source which has made
the data publicly available [18]. contains data collected for the period
2006 to December 2009 from which a dataset was compiled of 125,700 projects. "

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