Publication Type

Conference Proceeding Article

Version

Postprint

Publication Date

10-2010

Abstract

In this study, we extract patterns from a large developer collaborations network extracted from Source Forge. Net at high and low level of details. At the high level of details, we extract various network-level statistics from the network. At the low level of details, we extract topological sub-graph patterns that are frequently seen among collaborating developers. Extracting sub graph patterns from large graphs is a hard NP-complete problem. To address this challenge, we employ a novel combination of graph mining and graph matching by leveraging network-level properties of a developer network. With the approach, we successfully analyze a snapshot of Source Forge. Net data taken on September 2009. We present mined patterns and describe interesting

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing | Software Engineering

Research Areas

Data Management and Analytics; Software and Cyber-Physical Systems

Publication

WCRE 2010: 17th Working Conference on Reverse Engineering: 13-16 October 2010, Beverly, Massachusetts: Proceedings

First Page

269

Last Page

273

ISBN

9781424489114

Identifier

10.1109/WCRE.2010.38

Publisher

IEEE

City or Country

Piscataway, NJ

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1109/WCRE.2010.38

Share

COinS