Software source code sizing using fuzzy logic modeling

This study considers the applicability of fuzzy logic modeling methods to the task of software source code sizing, using a previously published data set and suggests that fuzzy predictive models can outperform their traditional regression-based counterparts.

Abstract

Knowing the likely size of a software product before it has been constructed is potentially beneficial in project management: for instance, size can be an important factor in determining an appropriate development/integration schedule, and it can be a significant input in terms of the allocation of personnel and other resources. In this study we consider the applicability of fuzzy logic modeling methods to the task of software source code sizing, using a previously published data set. Our results suggest that, particularly with refinement using data and knowledge, fuzzy predictive models can outperform their traditional regression-based counterparts.