Abstract
It is well documented that the software industry suffers from frequent cost overruns, and the software cost estimation remains a challenging issue. A contributing factor is, we believe, the inherent uncertainty of assessment of cost. Considering the uncertainty with cost drivers and representing the cost as a distribution of values can help us better understand the uncertainty of cost estimations and provide decision support for budge setting or cost control. In this paper, we use Bayesian belief networks to extend the COCOMO II for cost estimation with uncertainty, and construct the probabilistic cost model COCOMO-U. This model can be used to deal with the uncertainties of cost factors and estimate the cost probability distribution. We also demonstrate how the COCOMO-U is used to provide decision support for software development budget setting and cost control in a case study.
Supported by the National Natural Science Foundation of China under Grant No. 60573082; the National High-Tech Research and Development Plan of China under Grant No. 2005AA113140.
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References
Standish Group, Technical Report (2000), www.standishgroup.com/sample_research/PDFpages/extreme_chaos.pdf
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers, San Mateo (1988)
Pendharkar, P.C., Subramanian, G.H., Rodger, J.A.: A probabilistic Model for Predicting Software Development Effort. IEEE Transactions on Software Engineering 31(7) (2005)
Boehm, B.W., et al.: Software Cost Estimation with COCOMO II. Prentice Hall, Englewood Cliffs (2000)
Kitchenham, B., Pickard, L.M., Linkman, S., Jones, P.W.: Modeling Software Bidding Risks. IEEE Transactions on Software Engineering 29(6) (2003)
Moløkken-Østvold, K., Jørgensen, M.: A review of software surveys on software effort estimation. In: Proceedings of International Symposium on Empirical Software Engineering, pp. 223–230 (2003)
Greene, W.H.: Econometric Analysis. Prentice Hall, Englewood Cliffs (2000)
Kitchenham, B., Linkman, S.: Estimates, Uncertainty, and Risk. IEEE Software (May 1997)
Jørgensen, M.: Evidence-Based Guidelines for Assessment of Software Development Cost Uncertainty. IEEE Transactions on Software Engineering 31(11) (2005)
Lederer, A.L., Prasad, J.: A Causal Model for Software Cost Estimating Error. IEEE Transactions on Software Engineering 24(2) (1998)
Grimstad, S., Jørgensen, M., Moløkken-Østvold, K.: Software effort estimation terminology: The tower of Babel. Information and Software Technology (In Press) accepted, April 19 (2005)
Jørgensen, M., Teigen, K.H., et al.: Better Sure than Safe? Overconfidence in Judgment Based Software Development Effort Prediction Intervals. Journal of Systems and Software 70(1-2) (February 2004)
MusÃlek, P., Pedrycz, W., Sun, N., Succi, G.: On the Sensitivity of COCOMO II Software Cost Estimation Model. In: IEEE Symposium on Software Metrics (2002)
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Yang, D., Wan, Y., Tang, Z., Wu, S., He, M., Li, M. (2006). COCOMO-U: An Extension of COCOMO II for Cost Estimation with Uncertainty. In: Wang, Q., Pfahl, D., Raffo, D.M., Wernick, P. (eds) Software Process Change. SPW 2006. Lecture Notes in Computer Science, vol 3966. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11754305_15
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DOI: https://doi.org/10.1007/11754305_15
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