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Software Collaboration Networks - Complex Networks - Lecture Slides, Slides of Data Communication Systems and Computer Networks

During the course of the Complex Networks, we study the different concept regarding the complex computer networking. The main points upon which in these lecture slides focused are:Software Collaboration Networks, Background, Changes, Methodology, Data Collection, Network Topologies, Measures, Tools, Conclusion, Network Analysis

Typology: Slides

2012/2013

Uploaded on 04/23/2013

saraswathi
saraswathi 🇮🇳

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Download Software Collaboration Networks - Complex Networks - Lecture Slides and more Slides Data Communication Systems and Computer Networks in PDF only on Docsity!

Software Collaboration Networks

Overview

  • Introduction
  • Background
    • Changes
  • Methodology  Data Collection  Network Topologies  Measures  Tools Conclusion
  • Questions

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

Github Crawling

  • Using the Github API provides our data
  • Limited to 60 API calls per minute
  • Use multiple computers to collect all 1. million projects

Github Project Page

Developer/Project Network

Project-Developer Network

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

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

Conclusion

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