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Pierre Bourque, Serge Oligny, Alain Abran, Bertr, Fournier. Developing Project Duration Models in Software Engineering[J]. Journal of Computer Science and Technology, 2007, 22(3): 348-357.
Citation: Pierre Bourque, Serge Oligny, Alain Abran, Bertr, Fournier. Developing Project Duration Models in Software Engineering[J]. Journal of Computer Science and Technology, 2007, 22(3): 348-357.

Developing Project Duration Models in Software Engineering

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  • Received Date: March 14, 2006
  • Revised Date: December 04, 2006
  • Published Date: May 14, 2007
  • Based on the empirical analysis of data contained inthe International Software Benchmarking Standards Group (ISBSG)repository, this paper presents software engineering project durationmodels based on project effort.Duration models are built for the entire dataset and for subsets ofprojects developed for personal computer, mid-range and mainframeplatforms. Duration models are also constructed for projects requiringfewer than 400 person-hours of effort and for projects requiring morethan 400 person-hours of effort. The usefulness of adding the maximumnumber of assigned resources as a second independent variable toexplain duration is also analyzed. The opportunity to build durationmodels directly from project functional size in function points isinvestigated as well.
  • [1]
    Angelis L, Stamelos I, Morisio M. Building a software cost estimation model based on categorical data. In -\it Proc. Seventh International Software Metrics Symposium}, London, England, 2001, pp.415.
    [2]
    Boehm B W, Abts C, Chulani S. Software development cost estimation approaches. -\it Annals of Software Engineering}, 2000, 10(14): 177205.
    [3]
    Briand L, Langley T, Wieczorek I. A replicated assessment and comparison of common software cost modeling techniques. In -\it Proc. 22nd International Conference on Software Engineering (ICSE)}, Limerick, Ireland, 2000, pp.377386.
    [4]
    Dolado J J. On the problem of the software cost function. -\it Information and Software Technology}, 2001, 43(1): 6172.
    [5]
    Jeffery R, Ruhe M, Wieczorek I. A comparative technique of two software development cost modeling techniques using multi-organizational and company-specific data. -\it Information and Software Technology}, 2000, 42(14): 10091016.
    [6]
    Kitchenham B, Pfleeger S L, McColl B, Eagan S. An empirical study of maintenance and development estimation accuracy. -\it Journal of Systems and Software}, 2002, 64(1): 5777.
    [7]
    Smith R, Hale J E, Parrish A S. An empirical study using task assignment patterns to improve the accuracy of software estimation. -\it IEEE Transactions on Software Engineering}, 2001, 27(3): 264271.
    [8]
    Stewart B. Predicting project delivery rates using the naives-Bayes classifier. -\it Journal of Software Maintenance and Evolution: Research and Practice}, 2002, 14(3): 161179.
    [9]
    Wieczorek I, Ruhe M. How valuable is company specific data compared to multiple-company data for software cost estimation. In -\it Proc. Eighth IEEE Symposium on Software Metrics}, Ottawa, Canada, 2002, pp.237246.
    [10]
    Kitchenham B A, Pfleeger S L, Pickard L M \it et al. \rm Preliminary guidelines for empirical research in software engineering. -\it IEEE Transactions on Software Engineering}, 2002, 28(8): 721734.
    [11]
    Heemstra F J. Software cost estimation. -\it Information and Software Technology}, 1992, 34(10): 627639.
    [12]
    Kitchenham B. Empirical studies of assumptions that underlie software cost-estimation models. -\it Information and Software Technology}, 1992, 34(4): 211218.
    [13]
    Ferens D V. The conundrum of software estimation models. In -\it Proc. IEEE Aerospace and Electronic Systems Magazine}, 1999, pp.2329.
    [14]
    Jones C. Software cost estimation in 2002. -\it Crosstalk: The Journal of Defense Software Engineering}, 2002, 15(6).
    [15]
    Jones C. Determining software schedules. -\it Computer}, 1995, 28(2): 7375.
    [16]
    Park R E, Goethert W B, Webb J T. Software cost and schedule estimating: A process improvement initiative. -\it Software Engineering Institute}, Pittsburgh, U.S.A., 1994, http:// www.sei.cmu.edu/pub/documents/94.reports/pdf/sr03.94.pdf.
    [17]
    Lokan C, Wright T, Hill P, Stringer M. Organizational benchmarking using the ISBSG data repository. -\it IEEE Software}, 2001, 18(5): 2632.
    [18]
    Oligny S, Bourque P, Abran A. An empirical assessment of project duration models in software engineering. In -\it Proc. 8th European Software Control and Metrics Conference ESCOM}, Berlin, Germany, 1997.
    [19]
    Stensrud E, Foss T, Kitchenham B, Myrtveit I. An empirical validation of the relationship between the magnitude of relative error and project size. In -\it Proc. Eighth IEEE Symposium on Software Metrics}, Ottawa, Canada, 2002, pp.312.
    [20]
    D'Agostino R B, Belanger A, D'Agostino J. A suggestion for using powerful and informative tests of normality. -\it The American Statistician}, 1990, 44(4): 316321.
    [21]
    Boehm B W. Software Engineering Economics. Prentice Hall, 1981.
    [22]
    Neder J W W, Kutner M. Applied Linear Regression Model. 2nd Edition, Richard D (ed.), Homewood: Irwin Inc., IL, 1989.
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