A Pragmatic Cost Effective Model to Enhance the COCOMO Model in Software Estimation

This research work is aimed at to provide effective cost estimation methodology emphasize on cost effort and time . This paper summarizes the cost effort estimation of most conventionally used models like organic and semi-detached models using an improved version of genetic algorithm that enhances an empirical methodology to reduce the cost factor and time factor in software projects. Constructive cost model(Cocomo model) is broadly used for the fruitful valuation of cost estimation which is based on KLOC method(thousands of lines of code).This method yields beneficial result in case of lines of code method but lacks in terms of concept and logics. The same is estimated directly and is computed using the function point analysis. In the software development lifecycle, the software cost effort estimation is the most demanding process. The accuracy of the estimate in choosing the estimation model is an essential factor. Such conventional software effort estimation techniques fail to compute the accuracy of effort estimation and it is not up to the mark. So here, we tend to propose the cost reduction in the software projects by using the improved version of the known genetic algorithm.

Cost Estimate Model for Software Projects using GREYWOLF Algorithm and COCOMO Model

Cost estimation analysis for the software system project is the foremost difficult tasks in software organizations. In this paper, a comparison between an estimate and actual effort was done by applying the grey wolf’s algorithm to predict the effort and time of this software system for a given archive. The intermediate semi-detached COCOMO model was used with the grey wolf’s algorithm by taking the KLOC of the dataset as input, additionally to fifteen cost drivers and giving effort and time as output. The recommended model of the cost estimation helps the project manager by offering a fast and truly estimates the hassle and time of software system project which is nearer to the actual cost.