Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (7): 26-36.doi: 10.11896/jsjkx.250200108

• Computer Software • Previous Articles     Next Articles

Sub-community Detection and Evaluation in Open Source Projects:An Example of Apache IoTDB

WANG Weiwei1, LE Yang2, WANG Yankai1   

  1. 1 School of Software, Tsinghua University, Beijing 100084, China
    2 Department of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
  • Received:2025-02-26 Revised:2025-06-12 Published:2025-07-17
  • About author:WANG Weiwei,born in 1979,master.His main research interests include open source and industrial software.
  • Supported by:
    Chongqing Innovative Technology and Application Development Special Major Project(CSTB2023TIAD-STX0034).

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Abstract: As open-source collaboration has become a widely adopted paradigm in software development,the scale and structure of open-source projects have grown increasingly complex.Within the open-source collaboration model,ensuring software quality in large and intricate software systems has emerged as a critical issue.In the existing operational models of open-source communities,a project's community is often treated as a single entity,which contradicts the modular design principles of complex software.This study focuses on the phenomenon of sub-communities within open-source projects.Based on the analysis of code commit records and file change histories,a graph structure is constructed to model the relationships between developers and code files,upon which a sub-community detection algorithm is proposed that leverages developer activity and code modification records.By introducing intra-community participation coefficients and inter-community participation coefficients,this paper estab-lishes a core developer identification model,providing project managers with a quantitative evaluation tool for assessing developer contributions and collaboration significance.Additionally,it designs a sub-community scoring method that comprehensively considers both modular concentration and dispersion to evaluate the quality performance of different sub-communities in the module development process.An empirical analysis is conducted using the Apache IoTDB project as a case study.By mining 11 523 commit records from 282 developers,it constructs a collaboration network and identify four distinct sub-communities with significant characteristics.The experimental results indicate that the core developer identification outcomes and the code quality evaluation scores of each sub-community align with actual development conditions,validating the effectiveness of the proposed models and methods in open-source projects.

Key words: Open-source project, Collaboration network, Sub-community detection, Core developers, Apache IoTDB, Code quality evaluation

CLC Number: 

  • TP311
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