Software Collaboration Networks

SOFTWARE COLLABORATION

NETWORKSBy Chris Zachor

Overview

Introduction Background

Changes Methodology

Data Collection Network Topologies Measures Tools

Conclusion Questions

Introduction

Use network analysis to better understand the SourceForge and Github community developers

Identify key differences (if any) within the two communities

Examine the diversity of collaborations within these two communities

Changes

The addition of Github to the study Contains some of the same attributes to

allow for a comparison

Other communities were looked at, but they either were not large enough or did not provide enough public data.

Data Collection

Crawling the websites using a simple Perl script and regular expressions

Collect a project list from Sourceforge www.sourceforge.net/projects/projectTitle No specified request limit Check for duplicates

Sourceforge Project Page

Github Crawling

Using the Github API provides our data Limited to 60 API calls per minute Use multiple computers to collect all 1.5

million projects

Github Project Page

Github API

Developer/Project Network

Project-Developer Network

Measures and Metrics

Degree Clustering Coeficient Modularity Power Law Small World Phenomenon

Degree

Average number of projects worked on by a developer

Average number of collaborations Average number of developers on a

project

Clustering Coeficient

Examine how likely developers are to stick together in groups

Examine both average clustering coefficient for the entire network and the local clustering coefficient for nodes of interest

Modularity

Provide us with a measure of how diverse developer collaborations are.

Range -1 < Q < 1 Ranges closer to one show less diversity

in collaboration choices Ranges closer to negative one show more

diversity in collaboration choices

Power Law

Previous studies have found that the Sourceforge community does follow the power law

No such study has been done on the Github community

Fewer developers should be apart of many project while many developers should be involved with only one project

Small World Phenomenon

Previous studies have shown the Sourceforge community does exhibit small world properties

Once again, no study has been done on the Github community

Using Pajek, I will create a random network of the same nodes and edges

Then, compare the clustering coefficient and the average shortest path

Tools

Perl Pajek cURL wget GUESS

Conclusion

Through the use of network analysis, we hope to gain a better understanding of the developers of Sourceforge and Github communities.

Questions?

Suggestions?Comments?