Software analytics study of Open-Source system survivability through social contagion

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Free, Libre and Open Source Software (FLOSS) development has grown in prominence in recent years as the software development approach of choice. However, the factors responsible for maintaining development interest in them are still poorly understood, as FLOSS projects differ significantly from traditional for-profit closed-source software development. To address that knowledge gap, we have analyzed data from GitHub, an open source code repository which provides extensive records on a multitude of collaborative software engineering projects. Using machine learning algorithms, we sought out patterns in the data that might help us understand how projects survive. Our findings suggest that the impressions propagated by the users of software projects to other users strongly influence the projects' survival, as one would expect in a social contagion model.

Original languageBritish English
Title of host publicationIEEM 2015 - 2015 IEEE International Conference on Industrial Engineering and Engineering Management
PublisherIEEE Computer Society
Pages1213-1217
Number of pages5
ISBN (Electronic)9781467380669
DOIs
StatePublished - 18 Jan 2016
EventIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2015 - Singapore, Singapore
Duration: 6 Dec 20159 Dec 2015

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2016-January
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

ConferenceIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2015
Country/TerritorySingapore
CitySingapore
Period6/12/159/12/15

Keywords

  • social contagion
  • software project survival

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