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Abstract
In software development, effort estimation is the process of predicting the most realistic amount of effort (expressed in terms of person-hours or money) required to develop or maintain software based on incomplete, uncertain and noisy input.The various effort estimation models have been proposed in the recent times for effort estimation. Among various proposed techniques are neural network, use case diagrams are the popular techniques to estimate KLOC value. In this work, a novel technique is proposed for effort estimation, which is based on fusion of function point analysis and SLIM to estimate KLOC value. The simulation is performed to calculate MRE value of proposed and existing algorithms using NASA 93 dataset. It has been found that proposed technique performs well as compared to existing technique in terms of MRE value.