Publication Type
Encyclopaedia
Version
acceptedVersion
Publication Date
1-2018
Abstract
In this entry, we mine collaboration patterns from a large software developer network (Surian et al. 2010). We consider high- and low-level patterns. High-level patterns correspond to various network-level statistics that we observe to hold in this network. Low-level patterns are topological subgraph patterns that are frequently observed among developers collaborating in the network. Mining topological subgraph patterns are difficult as it is an NP-hard problem. To address this issue, we use a combination of frequent subgraph mining and graph matching by leveraging the power law property exhibited by a large collaboration graph. The technique is applicable to any software developer network that could be represented as a large graph. As a case study, we experiment with a developer collaboration network extracted from SourceForge.Net, which is the most popular open-source software portal.
Keywords
Collaboration patterns, Developer collaboration network, Graph pattern mining
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering
Publication
Encyclopedia of social network analysis and mining
Editor
R. Alhajj, & J. Rokne
First Page
224
Last Page
229
ISBN
9781493971312
Identifier
10.1007/978-1-4939-7131-2_292
Publisher
Springer
City or Country
Cham
Citation
SURIAN, Didi; LIM, Ee-peng; and LO, David.
Collaboration patterns in software developer network. (2018). Encyclopedia of social network analysis and mining. 224-229.
Available at: https://ink.library.smu.edu.sg/sis_research/4904
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-1-4939-7131-2_292
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons
