Collaboration patterns in software developer network

• Main Authors: SURIAN, Didi, LIM, Ee-peng, LO, David
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Collaboration patterns; Developer collaboration network; Graph pattern mining; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/4904; https://ink.library.smu.edu.sg/context/sis_research/article/5907/viewcontent/Collaboration_Patterns_in_Software_Developer_Network_av.pdf
• Institution: Singapore Management University

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.