• 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