TO DEVELOP AN EFFICIENT SOFTWARE COST ESTIMATION MODEL TO FORECAST LIKELY TOTAL COST OF PROJECTS

All computer-based systems rely heavily on software. The hardest part of developing software is figuring out how much it will cost. Estimating how much a piece of software will cost is an essential step in the development process. This study presents an improved fuzzy logic-based framework for dealing with early-stage data inaccuracies and uncertainties. The framework is based on the Cost Constructive methodology (COCOMO), an established cost estimate methodology. The COCOMO model is an empirical model developed from data from several software development initiatives. The estimating procedure is additionally bolstered by the use of the optimization method in fuzzy. The unique method uses the Particle Swarm Optimization (PSO) algorithm, which is an optimization algorithm. Mean Absolute Relative Error (MARE) is used to evaluate the effectiveness of the suggested system. The suggested technique is implemented in the JAVA platform, and the acquired results demonstrate that, in comparison to the prior approaches, the new method provides more accurate cost estimates.