A Statistical Approach for the Maximization of the Financial Benefits Yielded by a Large Set of MMFs and AEs
Antonio J. Alencar; Tércio Pacitti Intitute for Computer Research and Application Development, Federal University of Rio de Janeiro (UFRJ), Av. Athos da Silveira Ramos 274, 21941-916 Rio de Janeiro, RJ
Computing and Informatics, Tome 33 (2014) no. 1, / Harvested from
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.
Publié le : 2014-02-24
@article{cai2156,
     author = {Antonio J. Alencar; T\'ercio Pacitti Intitute for Computer Research and Application Development, Federal University of Rio de Janeiro (UFRJ), Av. Athos da Silveira Ramos 274, 21941-916 Rio de Janeiro, RJ},
     title = {A Statistical Approach for the Maximization of the Financial Benefits Yielded by a Large Set of MMFs and AEs},
     journal = {Computing and Informatics},
     volume = {33},
     number = {1},
     year = {2014},
     language = {en},
     url = {http://dml.mathdoc.fr/item/cai2156}
}

Antonio J. Alencar; Tércio Pacitti Intitute for Computer Research and Application Development, Federal University of Rio de Janeiro (UFRJ), Av. Athos da Silveira Ramos 274, 21941-916 Rio de Janeiro, RJ. A Statistical Approach for the Maximization of the Financial Benefits Yielded by a Large Set of MMFs and AEs. Computing and Informatics, Tome 33 (2014) no. 1, . http://gdmltest.u-ga.fr/item/cai2156/