An Examination of the Factors Influencing Software Development Effort

Authors: Zhizhong Jiang, Peter Naudé

Abstract:

Effective evaluation of software development effort is an important aspect of successful project management. Based on a large database with 4106 projects ever developed, this study statistically examines the factors that influence development effort. The factors found to be significant for effort are project size, average number of developers that worked on the project, type of development, development language, development platform, and the use of rapid application development. Among these factors, project size is the most critical cost driver. Unsurprisingly, this study found that the use of CASE tools does not necessarily reduce development effort, which adds support to the claim that the use of tools is subtle. As many of the current estimation models are rarely or unsuccessfully used, this study proposes a parsimonious parametric model for the prediction of effort which is both simple and more accurate than previous models.

Keywords: Development effort, function points, team size, development language, CASE tool, rapid application development.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1061286

References:

[1] R. S. Pressman, Software Engineering : A Practitioner's Approach. London: McGraw-Hill, 2005.
[2] J. C. Vliet, Software Engineering : Principles and Practice. Chichester: Wiley, 1993.
[3] N. R. Howes, "Managing software development projects for maximum productivity," IEEE Transactions on Software Engineering, vol. SE10, pp. 27-35, 1984.
[4] R. E. Loesh, "Improving productivity through standard design templates," Data Processing, vol. 27, pp. 57-59, 1985.
[5] D. N. Card, F. E. McGarry, and G. T. Page, "Evaluating software engineering technologies," IEEE Transactions on Software Engineering, vol. SE-13, pp. 845-851, 1987.
[6] G. R. Finnie, G. E. Wittig, and D. Petkov, "Prioritizing software development productivity factors using the analytic hierarchy process," Journal of Systems and Software, vol. 22, pp. 129-139, 1993.
[7] J. D. Blackburn, G. D. Scudder, and L. N. V. Wassenhove, "Improving speed and productivity of software development: a global survey of software developers," IEEE Transactions on Software Engineering, vol. 22, pp. 875-885, 1996.
[8] K. Maxwell, L. V. Wassenhove, and S. Dutta, "Software development productivity of European space, military and industrial applications," IEEE Transactions on Software Engineering, vol. 22, pp. 706-718, 1996.
[9] A. W. Brown, D. J. Carney, E. J. Morris, D. B. Smith, and P. F. Zarrella, Principles of CASE Tool Integration. New York: Oxford University Press, 1994.
[10] R. Klepper and D. Bock, "Third and fourth generation language productivity differences," Communications of the ACM, vol. 38, pp. 69- 79, 1995.
[11] D. Flynn, J. Vagner, and O. D. Vecchio, "Is CASE technology improving quality and productivity in software development?," Logistics Information Management, vol. 8, pp. 8-23, 1995.
[12] A. Lee, C. H. Cheng, and J. Balakrishnan, "Software development cost estimation: Integrating neural network with cluster analysis," Information & Management, vol. 34, pp. 1-9, 1998.
[13] K. Srinivasan and D. Fisher, "Machine learning approaches to estimating software development effort," IEEE Transactions on Software Engineering, vol. 21, pp. 126-137, 1995.
[14] R. D. Banker, H. Chang, and C. F. Kemerer, "Evidence on economies of scale in software development," Information and Software Technology, vol. 36, pp. 275-282, 1994.
[15] A. R. Venkatachalam, "Software cost estimation using artificial neural networks," presented at 1993 International Joint Conference on Neural Networks, Nagoya, Japan, 1993.
[16] G. H. Subramanian, P. C. Pendharkar, and M. Wallace, "An empirical study of the effect of complexity, platform, and program type on software development effort of business applications," Empirical Software Engineering, vol. 11, pp. 541-553, 2006.
[17] S. Kumar, B. A. Krishna, and P. S. Satsangi, "Fuzzy systems and neural networks in software engineering project management," Journal of Applied Intelligence, vol. 4, pp. 31-52, 1994.
[18] R. W. Selby and A. A. Porter, "Learning from examples: generation and evaluation of decision trees for software resource analysis," IEEE Transactions on Software Engineering, vol. 14, pp. 1743-1757, 1988.
[19] B. W. Boehm, T. E. Gray, and T. Seewaldt, "Prototyping vs. specifying: A multi-project experiment," presented at 7th International Conference on Software Engineering, Orlando, 1984.
[20] K. Maxwell, L. Van Wassenhove, and S. Dutta, "Performance Evaluation of General and Company Specific Models in Software Development Effort Estimation," Management Science, vol. 45, pp. 787- 803, 1999.
[21] M. van Genuchten and H. Koolen, "On the use of software cost models," Information & Management, vol. 21, pp. 37-44, 1991.
[22] T. K. Abdel-Hamid, "Adapting, correcting, and perfecting software estimates: Amaintenance metaphor " in Computer, vol. 26, 1993, pp. 20- 29
[23] A. J. Albrecht and J. E. G. Gaffney, "Software function, source lines of code, and development effort prediction: A software science validation," IEEE Transactions on Software Engineering, vol. SE-9, pp. 639-648, 1983.
[24] J. E. Matson, B. E. Barrett, and J. M. Mellichamp, "Software development cost estimation using function points," IEEE Transactions on Software Engineering, vol. 20, pp. 275-286, 1994.
[25] F. J. Heemstra, "Software cost estimation," Information and Software Technology, vol. 34, pp. 627-639, 1992.
[26] H. A. Rubin, "Macroestimation of software development parameters: the ESTIMACS systems.," in SOFTAIR Conference on Software Development Tools, Techniques, and Alternatives,. New York: IEEE Press, 1983, pp. 109-118.
[27] N. Fenton, "Software measurement: A necessary scientific basis," IEEE Transactions on Software Engineering, vol. 20, pp. 199-206, 1994.
[28] N. D. Singpurwalla, Statistical Methods in Software Engineering: Reliability and Risk. London: Springer, 1999.
[29] A. Heiat and N. Heiat, "A model for estimating efforts required for developing small-scale business applications," Journal of Systems and Software, vol. 39, pp. 7-14, 1997.
[30] C. F. Kemerer, "Reliability of function points measurement: a field experiment," Communications of the ACM, vol. 36, pp. 85-97, 1993.
[31] C. R. Symons, "Function point analysis: difficulties and improvements," IEEE Transactions on Software Engineering, vol. 14, pp. 2-11, 1988.
[32] C. F. Kemerer and B. S. Porter, "Improving the reliability of function point measurement: an empirical study," IEEE Transactions on Software Engineering, vol. 18, pp. 1011-1024, 1992.
[33] F. Walkerden and R. Jeffery, "An empirical study of analogy-based software effort estimation," Empirical Software Engineering, vol. 4, pp. 135-158, 1999.
[34] B. A. Kitchenham, R. T. Hughes, and S. G. Linkman, "Modeling software measurement data," IEEE Transactions on Software Engineering, vol. 27, pp. 788-804, 2001.
[35] S. D. Conte, H. E. Dunsmore, and Y. E. Shen, Software Engineering Metrics and Models. Redwood City, CA: Benjamin-Cummings Publishing, 1986.
[36] F. Louis, "Team size and productivity in systems development," Information Systems Management, vol. 8, pp. 27-35, 1991.
[37] E. Mendes and B. Kitchenham, "Web Productivity Measurement and Benchmarking," in Web Engineering, E. Mendes and N. Mosley, Eds. Berlin: Springer, 2006, pp. 75-106.
[38] L. B. Wilson and R. G. Clark, Comparative Programming Languages. Wokingham: Addison-Wesley, 1988.
[39] R. T. Yeh, "Notes on concurrent engineering," IEEE Transactions on Knowledge and Data Engineering, vol. 4, pp. 407-414, 1992.
[40] T. Bruckhaus, N. H. Madhavii, I. Janssen, and J. Henshaw, "The impact of tools on software productivity," IEEE Software, vol. 13, pp. 29-38, 1996.
[41] J. Martin, Rapid Application Development. New York: Macmillan, 1991.
[42] G. H. Subramanian and G. E. Zarnich, "An examination of some software development effort and productivity determinants in ICASE tool projects," Journal of Management Information Systems, vol. 12, pp. 143-160, 1996.
[43] P. Beynon-Davies, C. Carne, H. Mackay, and D. Tudhope, "Rapid application development (RAD): An empirical review," European Journal of Information Systems, vol. 8, pp. 211-223, 1999.
[44] B. Boehm, C. Abts, and S. Chulani, "Software development cost estimation approaches-A survey," Annals of Software Engineering, vol. 10, pp. 177-205, 2000.
[45] Q. Liu and R. C. Mintram, "Preliminary data analysis methods in software estimation," Software Quality Journal, vol. 13, pp. 91-115, 2005.
[46] C. F. Kemerer and S. Slaughter, "Determinants of software maintenance profiles: An empirical investigation," Journal of Software Maintenance, vol. 9, pp. 235-251, 1997.
[47] W. Harrison, "A flexible method for maintaining software metrics data: a universal metrics repository," Journal of Systems and Software, vol. 72, pp. 225-234, 2004.
[48] C. J. Lokan, "An empirical analysis of function point adjustment factors," Information and Software Technology, vol. 42, pp. 649-660, 2000.
[49] R. Jeffery, M. Ruhe, and I. Wieczorek, "A comparative study of two software development cost modeling techniques using multiorganizational and company-specific data," Information and Software Technology, vol. 42, pp. 1009-1016, 2000.
[50] J. J. Cuadrado-Gallego, M. Sicilia, M. Garre, and D. Rodríguez, "An empirical study of process-related attributes in segmented software costestimation relationships," Journal of Systems and Software, vol. 79, pp. 353-361, 2006.
[51] J. Moses, M. Farrow, N. Parrington, and P. Smith, "A productivity benchmarking case study using Bayesian credible intervals," Software Quality Journal, vol. 14, pp. 37-52, 2006.
[52] NESMA, NESMA FPA Counting Practices Manual 2.0: Nesma Association, 1996.
[53] S. A. Green, "How many subjects does it take to do a multiple regression analysis?," Multivariate Behavioral Research, vol. 26, pp. 499-510, 1991.
[54] W. N. Venables and B. D. Ripley, Modern applied statistics with S. New York: Springer, 2002.
[55] A. C. Rencher, Linear Models in Statistics. New York: John Wiley & Sons, 2000.
[56] W. J. Krzanowski, An Introduction to Statistical Modelling. London: Arnold, 1998.
[57] R. E. Yellen, "Systems analysts performance using CASE versus manual methods," presented at Proceedings of the Twenty-Third Annual Hawaii International Conference on System Sciences, Kailua-Kona, Hawaii, 1990.
[58] R. J. Norman, G. F. Corbitt, M. C. Butler, and D. D. McElroy, "CASE technology transfer: A case study of unsuccessful change," Journal of Systems Management, vol. 40, pp. 33-37, 1989.
[59] W. J. Orlikowski, "CASE Tools and the IS workplace: Some findings form empirical research," presented at Proceedings of the ACM SIGCPR Conference on Management of Information Systems Personnel, College park, Maryland, 1988.
[60] I. Vessey, S. L. Jarvenpaa, and N. Tractinsky, "Evaluation of vendor products: CASE tools as methodology companions," Communications of the ACM, vol. 35, pp. 90-105, 1992.
[61] D. Hough, "Rapid delivery: An evolutionary approach for application development," IBM Systems Journal, vol. 32, pp. 397-419, 1993.