DocumentCode :
3237179
Title :
Mining Collaboration Patterns from a Large Developer Network
Author :
Surian, Didi ; Lo, David ; Lim, Ee-Peng
Author_Institution :
Sch. of Inf. Syst., Singapore Manage. Univ., Singapore, Singapore
fYear :
2010
fDate :
13-16 Oct. 2010
Firstpage :
269
Lastpage :
273
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 observations.
Keywords :
data mining; graph theory; groupware; statistical analysis; Source Forge. Net; collaboration pattern mining; graph matching; graph mining; hard NP-complete problem; large developer network; network-level statistics; topological subgraph pattern; Collaboration; Data mining; Databases; Pattern matching; Programming; Runtime; Software; Collaboration Patterns; Developer Networks; Distributed Software Development; Graph Matching; Graph Mining; Network Mining; Open Source Projects;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reverse Engineering (WCRE), 2010 17th Working Conference on
Conference_Location :
Beverly, MA
ISSN :
1095-1350
Print_ISBN :
978-1-4244-8911-4
Type :
conf
DOI :
10.1109/WCRE.2010.38
Filename :
5645568
Link To Document :
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