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Observations on patterns of development in open source software projects

Published: 17 May 2005 Publication History

Abstract

This paper discusses a project aimed at understanding how open source software evolves by examining patterns of development and changes in releases over time. The methodological approach of the research and initial observations are described. These include descriptions of release cycles and categorization of projects based on the overall changes in size and complexity exhibited across releases. Implications of these observations are discussed in light of prior and future work on understanding OSS evolution.

References

[1]
Belady, L. A., and Lehman, M. M. A Model of Large Program Development. IBM Systems Journal, 3, (1976) 225--252.
[2]
Bennett, K. H.; Knight, C.; Munro, M.; and Xu, J. Centres of Excellence: Research Institute in Software Evolution, University of Durham. Computing and Control Engineering Journal, 11, 4 (2000) 179--186.
[3]
Boehm, B. Software Engineering Economics. Englewood Cliffs, NJ: Prentice Hall, 1981.
[4]
Darcy, D. P.; Kemerer, C.; Slaughter, S. A.; and Tomayko The Structural Complexity of Software: An Empirical Test. University of Maryland, Smith School of Business Working Paper, (2005)
[5]
Godfrey, M. W., and Tu, Q. Evolution in Open Source Software: A Case Study, in Proceedings of International Conference Software Maintenance, San Jose, California, 2000, 131--142.
[6]
Godfrey, M. W., and Tu, Q. Growth, Evolution, and Structural Change in Open Source Software, in Proceedings of International Conference on Software Engineering, 4th International workshop on Principles of Software Evolution, 2002, ACM Press 103--106.
[7]
Goldin, D. S. Taming Software Complexity Is Critical, Design News, Vol. 56, No. 1, January 8 (2001), 172.
[8]
Gonzalez-Barahona, J. M.; Perez, M. A. O.; Quiros, P. d. i. H.; Gonzalez, J. C.; and Olivera, V. M. Counting Potatoes: The Size of Debian 2.2, Upgrade Magazine, Vol. II, No. 6, (2001),
[9]
Gorla, N., and Ramakrishnan, R. Effect of Software Structure Attributes Software Development Productivity. Journal of Systems and Software, 36, 2 (1997) 191--199.
[10]
Howison, J., and Crowston, K. The Perils and Pitfalls of Mining Sourceforge. in Proceedings of International Conference on Software Engineering, Mining Software Repositories Workshop, Edinburgh, 2004.
[11]
Kemerer, C. F. Software Complexity and Software Maintenance: A Survey of Empirical Research. Annals of Software Engineering, 1, 1 (1995) 1--22.
[12]
Kemerer, C. F., and Slaughter, S. A. An Empirical Approach to Studying Software Evolution. IEEE Transactions on Software Engineering, 25, 4 (1999) 493--509.
[13]
Kemerer, C. F., and Slaughter, S. A. An Empirical Approach to Studying Software Evolution. TSE, 25, 4 (1999) 493--509.
[14]
Koch, S., and Schneider, G. Results from Software Engineering Research into Open Source Development Projects Using Public Data. Diskussion zum Tagigkeitsfeld Informationverarbeitung und Informationswirtschaft, 22, (2000) 1--16.
[15]
Lehman, M. M., and Ramil, J. F. An Approach to a Theory of Software Evolution, in Proceedings of Proc. 2001 Intern Workshop on Principles of Software Evolution, 2001.
[16]
Paulson, J.; Succi, G.; and Eberlein, A. An Empirical Study of Open Source and Closed Source Software Products. IEEE Transactions in Software Engineering, 30, 4 (2004) 246--256.
[17]
Prahalad, C. K., and Krishnan, M. S. The New Meaning of Quality in the Information Age. Harvard Business Review, (1999) 109--118.
[18]
Raymond, E. S. The Cathedral and the Bazaar: Musing on Linux and Open Source by an Accidental Revolutionary. Sabastopol, CA: O'Reilly, 2001.
[19]
Scacchi, W. Understanding the Requirements for Developing Open Source Software Systems. IEE Proceedings on Software, 149, 1 (2002) 24--39.
[20]
Scacchi, W. Understanding Open Source Software Evolution, (2004). http://www.ics.uci.edu/~wscacchi/Papers/New/Understandin g-OSS-Evolution.pdf
[21]
Zhao, L., and Elbaum, S. Quality Assurance under the Open Source Development Model. Journal of Systems and Software, 66, (2003) 65--75.

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Published In

cover image ACM SIGSOFT Software Engineering Notes
ACM SIGSOFT Software Engineering Notes  Volume 30, Issue 4
July 2005
1514 pages
ISSN:0163-5948
DOI:10.1145/1082983
Issue’s Table of Contents
  • cover image ACM Other conferences
    5-WOSSE: Proceedings of the fifth workshop on Open source software engineering
    May 2005
    74 pages
    ISBN:1595931279
    DOI:10.1145/1083258
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 May 2005
Published in SIGSOFT Volume 30, Issue 4

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Author Tags

  1. open source software
  2. software evolution

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Cited By

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  • (2018)Test effort estimation and prediction of traditional and rapid release models using machine learning algorithmsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-16970335:2(1657-1669)Online publication date: 1-Jan-2018
  • (2016)Towards quality gates in continuous delivery and deployment2016 IEEE 24th International Conference on Program Comprehension (ICPC)10.1109/ICPC.2016.7503737(1-4)Online publication date: May-2016
  • (2015)Understanding the impact of rapid releases on software qualityEmpirical Software Engineering10.1007/s10664-014-9308-x20:2(336-373)Online publication date: 1-Apr-2015
  • (2012)Do faster releases improve software quality?Proceedings of the 9th IEEE Working Conference on Mining Software Repositories10.5555/2664446.2664475(179-188)Online publication date: 2-Jun-2012
  • (2008)Self-organization process in open-source softwareInformation and Software Technology10.1016/j.infsof.2007.02.01850:5(361-374)Online publication date: 1-Apr-2008
  • (2014)Statistical analysis of popular open source software projects and their communities2014 6th International Conference on Information Technology and Electrical Engineering (ICITEE)10.1109/ICITEED.2014.7007913(1-6)Online publication date: Oct-2014
  • (2012)Do faster releases improve software quality? An empirical case study of Mozilla Firefox2012 9th IEEE Working Conference on Mining Software Repositories (MSR)10.1109/MSR.2012.6224279(179-188)Online publication date: Jun-2012
  • (2007)Open Source SoftwareHandbook of Research on Open Source Software10.4018/978-1-59140-999-1.ch015(184-196)Online publication date: 2007
  • (2007)Using Repository of Repositories (RoRs) to Study the Growth of F/OSS Projects: A Meta-Analysis Research ApproachOpen Source Development, Adoption and Innovation10.1007/978-0-387-72486-7_12(147-160)Online publication date: 2007

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