Software cost estimation with fuzzy models

TLDR: A fuzzy set-based generalization of the COCOMO model is concerned with, augmenting the model by admitting software systems to belong partially to the three main categories and discussing key implications of this generalization and its links with a generalized sensitivity analysis.

Abstract: Estimation of effort/cost required for development of software products is inherently associated with uncertainty In this paper, we are concerned with a fuzzy set-based generalization of the COCOMO model (f-COCOMO) The inputs of the standard COCOMO model include an estimation of project size and an evaluation of other parameters Rather than using a single number, the software size can be regarded as a fuzzy set (fuzzy number) yielding the cost estimate also in form of a fuzzy set The paper includes detailed results with this regard by relating fuzzy sets of project size with the fuzzy set of effort The analysis is carried out for several commonly encountered classes of membership functions (such as triangular and parabolic fuzzy sets) The issue of designer-friendliness of the f-COCOMO model is discussed in detail Here we emphasize a way of propagation of uncertainty and ensuing visualization of the resulting effort (cost) Furthermore we augment the model by admitting software systems to belong partially to the three main categories (namely embedded, semidetached and organic) and discuss key implications of this generalization and highlight its links with a generalized sensitivity analysis The experimental part of the study illustrates the approach and contrasts it with the standard numeric version of the COCOMO model