@article{Alencar_Franco_Schmitz_Correa_2014, title={A Statistical Approach for the Maximization of the Financial Benefits Yielded by a Large Set of MMFs and AEs}, volume={32}, url={https://www.cai.sk/ojs/index.php/cai/article/view/2156}, abstractNote={This article introduces a statistical approach for the maximization of the financial benefits yielded by software projects that have been broken down into a considerable number of minimum marketable features modules (MMFs) and architectural elements (AEs). As the statistical approach requires a polynomial computational effort to run and provides approximation solutions with an arbitrarily chosen degree of confidence, it allows managers and developers to be more confident about the rightness of the decisions they make with little additional computational effort.}, number={6}, journal={COMPUTING AND INFORMATICS}, author={Alencar, Antonio J. and Franco, Carlos A. S. and Schmitz, Eber A. and Correa, Alexandre L.}, year={2014}, month={Feb.}, pages={1147–1169} }