Stochastic cost estimation and risk analysis in managing software projects
Connor, AM; MacDonell, SG
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This paper presents an overview of the use of stochastic modelling as an approach to assessing the impact of uncertainty in effort and cost estimations in software projects. Uncertainty in input values is modelled using probability distributions and this uncertainty is propagated through the model to provide risk information using Monte Carlo simulation. Statistical analysis of the outputs of the simulation provides a means for identifying where the highest risk in the estimates lies. Understanding this risk, in terms of both its impact and its likelihood, allows activities to be undertaken to mitigate the risk prior to submitting a tender, therefore increasing the confidence with which the bid/no-bid decision is made.