Fuzzy Logic for Enhancing the Sensitivity of COCOMO Cost Model

The accuracy of algorithmic models for software cost prediction is limited due to their inability to handle imprecision and uncertainties associated with the software project attributes like size, programmer experience, etc. This paper enhances the accuracy and sensitivity of one of a widely used models COCOMO81 intermediate by incorporating a fuzzy component into the model. The fuzzy component deals with the vagueness and imprecision of the model’s cost drivers. MATLAB fuzzy toolbox was used in implementing the proposed fuzzy model. Artificial datasets was derived from COCOMONASA2 dataset to evaluate the proposed fuzzy model. The results showed that the sensitivity of the proposed fuzzy model is superior to COCOMO81 intermediate. It’s worth mentioning that the idea of the paper isn’t restricted to COCOMO81 intermediate; it could be applied to other algorithmic models.