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Performance Evaluation of General and Company Specific Models in Software Development Effort Estimation

Author

Listed:
  • Katrina Maxwell

    (INSEAD, Boulevard de Constance, 77305 Fontainebleau Cedex, France)

  • Luk Van Wassenhove

    (INSEAD, Boulevard de Constance, 77305 Fontainebleau Cedex, France)

  • Soumitra Dutta

    (INSEAD, Boulevard de Constance, 77305 Fontainebleau Cedex, France)

Abstract

In this paper we present the results of our effort estimation analysis of a European Space Agency database consisting of 108 software development projects. We develop and evaluate simple empirical effort estimation models that include only those productivity factors found to be significant for these projects and determine if models based on a multicompany database can be successfully used to make effort estimations within a specific company. This was accomplished by developing company specific effort estimation models based on the significant productivity factors of a particular company and by comparing the results with those from general ESA models on a holdout sample of the company. To our knowledge, no other published research has yet developed and analysed software development effort estimation models in this way. Effort predictions made on a holdout sample of the individual company's projects using general models were less accurate than the company specific model. However, it is likely that in the absence of enough resources and data for a company to develop its own model, the application of general models may be more accurate than the use of guessing and intuition.

Suggested Citation

  • Katrina Maxwell & Luk Van Wassenhove & Soumitra Dutta, 1999. "Performance Evaluation of General and Company Specific Models in Software Development Effort Estimation," Management Science, INFORMS, vol. 45(6), pages 787-803, June.
    • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:6:p:787-803
    DOI: 10.1287/mnsc.45.6.787
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    References listed on IDEAS

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    1. Rajiv D. Banker & Srikant M. Datar & Chris F. Kemerer, 1991. "A Model to Evaluate Variables Impacting the Productivity of Software Maintenance Projects," Management Science, INFORMS, vol. 37(1), pages 1-18, January.
    2. Michael A. Cusumano & Chris F. Kemerer, 1990. "A Quantitative Analysis of U.S. and Japanese Practice and Performance in Software Development," Management Science, INFORMS, vol. 36(11), pages 1384-1406, November.
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    Cited by:

    1. Haruvy Ernan E & Wu Fang & Chakravarty Sujoy, 2005. "Incentives for Developers’ Contributions and Product Performance Metrics in Open Source Development: An Empirical Exploration," IIMA Working Papers WP2005-03-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    2. Yixin Qiu & Anandasivam Gopal & Il-Horn Hann, 2017. "Logic Pluralism in Mobile Platform Ecosystems: A Study of Indie App Developers on the iOS App Store," Information Systems Research, INFORMS, vol. 28(2), pages 225-249, June.
    3. M. S. Krishnan & C. H. Kriebel & Sunder Kekre & Tridas Mukhopadhyay, 2000. "An Empirical Analysis of Productivity and Quality in Software Products," Management Science, INFORMS, vol. 46(6), pages 745-759, June.
    4. Nishtha Langer & Sandra A. Slaughter & Tridas Mukhopadhyay, 2014. "Project Managers' Practical Intelligence and Project Performance in Software Offshore Outsourcing: A Field Study," Information Systems Research, INFORMS, vol. 25(2), pages 364-384, June.
    5. Rajiv D. Banker & Robert J. Kauffman, 2004. "50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science," Management Science, INFORMS, vol. 50(3), pages 281-298, March.

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