Mining collaboration patterns from a large developer network

• Main Authors: SURIAN, Didi, LO, David, LIM, Ee Peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2010
• Subjects: Databases and Information Systems; Numerical Analysis and Scientific Computing; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/1339; https://ink.library.smu.edu.sg/context/sis_research/article/2338/viewcontent/wcre10.pdf
• Institution: Singapore Management University

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