A Statistical Approach for the Maximization of the Financial Benefits Yielded by a Large Set of MMFs and AEs

Authors

  • 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
  • Carlos A. S. Franco 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
  • Eber A. Schmitz 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
  • Alexandre L. Correa Department of Applied Informatics, Federal University of the State of Rio de Janeiro (UNIRIO), Av. Pasteur 458, 22290-240 Rio de Janeiro, RJ

Keywords:

Value-based software engineering, incremental funding method, minimum marketable features, scheduling algorithms, software project appraisal

Abstract

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.

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How to Cite

Alencar, A. J., Franco, C. A. S., Schmitz, E. A., & Correa, A. L. (2014). A Statistical Approach for the Maximization of the Financial Benefits Yielded by a Large Set of MMFs and AEs. Computing and Informatics, 32(6), 1147–1169. Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/2156

Issue

Vol. 32 No. 6 (2013): Computing and Informatics

Section

Articles