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Socio-technical developer networks: should we trust our measurements?

Published:21 May 2011Publication History

ABSTRACT

Software development teams must be properly structured to provide effectiv collaboration to produce quality software. Over the last several years, social network analysis (SNA) has emerged as a popular method for studying the collaboration and organization of people working in large software development teams. Researchers have been modeling networks of developers based on socio-technical connections found in software development artifacts. Using these developer networks, researchers have proposed several SNA metrics that can predict software quality factors and describe the team structure. But do SNA metrics measure what they purport to measure? The objective of this research is to investigate if SNA metrics represent socio-technical relationships by examining if developer networks can be corroborated with developer perceptions. To measure developer perceptions, we developed an online survey that is personalized to each developer of a development team based on that developer's SNA metrics. Developers answered questions about other members of the team, such as identifying their collaborators and the project experts. A total of 124 developers responded to our survey from three popular open source projects: the Linux kernel, the PHP programming language, and the Wireshark network protocol analyzer. Our results indicate that connections in the developer network are statistically associated with the collaborators whom the developers named. Our results substantiate that SNA metrics represent socio-technical relationships in open source development projects, while also clarifying how the developer network can be interpreted by researchers and practitioners.

References

  1. A. Begel, Y. P. Khoo, and T. Zimmermann, "Codebook: Discovering and Exploiting Relationships in Software Repositories," in Int'l Conference on Software Engineering (ICSE), Cape Town, South Africa, 2010, p. 125--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. C. Bird, A. Gourley, P. Devanbu et al., "Mining Email Social Networks in Postgres," in Mining Software Repositories, Shanghai, China, 2006, p. 185--186. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. C. Bird, N. Nagappan, P. Devanbu et al., "Does Distributed Development Affect Software Quality? An Empirical Case Study of Windows Vista," Comm. of the ACM, vol. 52, no. 8, p. 85--93, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. C. Bird, D. Pattison, R. D'Souza et al., "Latent Social Structures in Open Source Projects," in FSE, Atlanta, GA, 2008, p. p24--36. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. U. Brandes, and T. Erlebach, Network Analysis: Methodological Foundations, Berlin: Springer, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. T. G. Cummings, "Self-Regulating Work Groups: A Socio-Technical Synthesis" The Academy of Management Review, vol. 3, no. 3, p. 625--634, 1978.Google ScholarGoogle ScholarCross RefCross Ref
  7. A. Meneely, M. Corcoran, and L. Williams, "Improving Developer Activity Metrics with Issue Tracking Annotations," in Workshop on Emerging Trends in Software Metrics (WETSoM), Cape Town, South Africa, 2010, p. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. A. Meneely, and L. Williams, "Secure Open Source Collaboration: An Empirical Study of Linus' Law" in Computer and Communications Security, Chicago, IL, 2009, p. 453--462. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. A. Meneely, and L. Williams, "Strengthening the Empirical Analysis between Developer Collaboration and Software Security," in Empirical Software Engineering & Measurement (ESEM), Bolzano-Bozen, Italy, 2010, p. to appear. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. A. Meneely, L. Williams, J. Osborne et al., "Predicting Failures with Developer Networks and Social Network Analysis " in Foundations in Software Engineering, Atlanta, GA, 2008, p. 13--23. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. N. Nagappan, B. Murphy, and V. R. Basili, "The Influence of Organizational Structure on Software Quality," in International Conference on Software Engineering, Leipzig, Germany, 2008, p. 521--530. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. R. Nia, C. Bird, P. Devanbu et al., "Validity of Network Analyses in Open Source Projects," in Mining Software Repositories, Cape Town, South Africa, 2010, p.Google ScholarGoogle Scholar
  13. M. Pinzger, N. Nagappan, and B. Murphy, "Can Developer-Module Networks Predict Failures?," in Foundations in Software Engineering, Atlanta, GA, 2008, p. 2--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. E. S. Raymond, The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary, Sebastopol, California: O'Reilly and Associates, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. A. Sarma, L. Maccherone, P. Wagstrom et al., "Tesseract: Interactive visual exploration of socio-technical relationships in software development," in Proceedings of the 2009 IEEE 31st International Conference on Software Engineering, 2009, pp. 22--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Y. Shin, A. Meneely, L. Williams et al., "Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities," IEEE Transactions in Software Engineering (TSE), vol. to appear, no. p. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. E. Trist, and K. Bamforth, "Some social and psychological consequences of the longwall method of coal getting," Human Relations, vol. 4, no. 1, p. 3--38, 1951.Google ScholarGoogle ScholarCross RefCross Ref
  18. T. Wolf, A. Schroter, D. Damian et al., "Predicting build failures using social network analysis on developer communication," in Proceedings of the 2009 IEEE 31st International Conference on Software Engineering, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        cover image ACM Conferences
        ICSE '11: Proceedings of the 33rd International Conference on Software Engineering
        May 2011
        1258 pages
        ISBN:9781450304450
        DOI:10.1145/1985793

        Copyright © 2011 ACM

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        Publication History

        • Published: 21 May 2011

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