Modeling success in FLOSS project groups

Justin M. Beaver, Xiaohui Cui, Jesse L. St Charles, Thomas E. Potok

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

8 Scopus citations

Abstract

A significant challenge in software engineering is accurately modeling projects in order to correctly forecast success or failure. The primary difficulty is that software development efforts are complex in terms of both the technical and social aspects of the engineering environment. This is compounded by the lack of real data that captures both the measures of success in performing a process, and the measures that reflect a group's social dynamics. This research focuses on the development of a model for predicting software project success that leverages the wealth of available open source project data in order to accurately forecast the behavior of those software engineering groups. The model accounts for both the technical elements of software engineering and the social elements that drive the decisions of individual developers. Agent-based simulations are used to represent the complexity of the group interactions, and the behavior of each agent is based on the acquired open source software engineering data. For four of the five project success measures, the results indicate that the developed model represents the underlying data well and provides accurate predictions of open source project success indicators.

Original languageEnglish
Title of host publicationPROMISE 2009 - International Conference on Predictor Models in Software Engineering
DOIs
StatePublished - 2009
Event5th International Conference on Predictor Models in Software Engineering, PROMISE '09 - Vancouver, BC, Canada
Duration: May 18 2009May 19 2009

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Conference on Predictor Models in Software Engineering, PROMISE '09
Country/TerritoryCanada
CityVancouver, BC
Period05/18/0905/19/09

Keywords

  • Bayesian belief networks
  • FLOSS
  • agent-based simulation
  • data-based models
  • software engineering

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