Uma Investigação de Modelos de Estimativas de Esforço em Gerenciamento de Projeto de Software

Iris Fabiana de Barcelos TrontoJosé Demísio Simões da SilvaNilson Sant’Anna

Accurate estimation in software project management is critical. Fundamental measurements are size, effort, resources, cost, and time spent in the software development process. Underestimates can lead to time pressures that compromise full functional development and thorough testing of software. Likewise, overestimates can result in noncompetitive bids. In this paper, predictive artificial neural network and stepwise regression based models are investigated, with the goal of offering an alternative for those who do not believe in estimation models. The results presented in this paper compare the performance of both methods and indicate that these techniques are competitive with the methods of APF, SLIM, and COCOMO.

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