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

In: Computing and Informatics, vol. 32, no. 6

A.j. Alencar - C.a.s. Franco - E.a. Schmitz - A.l. Correa

Details:

Year, pages: 2013, 1147 - 1169

Keywords:

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

About article:

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.

How to cite:

ISO 690:

Alencar, A., Franco, C., Schmitz, E., Correa, A. 2013. A Statistical Approach for the Maximization of the Financial Benefits Yielded by a Large Set of MMFs and AEs. In Computing and Informatics, vol. 32, no.6, pp. 1147-1169. 1335-9150.

APA:

Alencar, A., Franco, C., Schmitz, E., Correa, A. (2013). 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. 1335-9150.