Enrichment of accurate software effort estimation using fuzzy-based function point analysis in business data analytics

Accurate effort estimation is a significant task in software development, which is helpful in the scheduling and tracking of the project. A number of estimation models are available for effort calculation. However, a lot of newer models are still being proposed to obtain more accurate estimation. This paper attempts to propose a hybrid technique which incorporates both quality factors and fuzzy-based technique in function point analysis. Fuzzy logic has the capability of tackling the uncertainty issues in the estimation. The goal of this paper is to evaluate the accuracy of fuzzy analysis for software effort estimation. In this approach, fuzzy logic is used to control the uncertainty in the software size with the help of a triangular fuzzy set, and defuzzification through the weighted average method. The experimentation is done with different project data on the proposed model, and the results are tabulated. The measured effort of the proposed model is compared with that of the existing model, and finally, the performance evaluation is done based on parameters in terms of MMRE and VAF.