Abstract:

Software engineering is a hot and needed research area for early and also accurate estimation of cost, effort, time to achieving quality of software project. Accuracy is the primary factor involving victim of software cost estimation and increasing the productivity of any workstation. Algorithmic and non-algorithmic models are helped to predict the cost in earlier stage without optimizing any constraints. Nowadays new optimization algorithms based on both the nature inspired based and swarm intelligence based are help to introduce new cost, effort and time estimation in earlier stage of design efficiently. Here, under estimation and over estimation should be optimized using new meta-heuristic algorithm inspired by Duck Flock. For the proposed algorithm eDTO, ACC (Accuracy), VAR (Variance), metrics are used to evaluating the results using NASA 93 standard dataset. Evaluation results are compared with existing COCOMO, NN, SBA and proved that the eDTO having high accuracy and low miscalculation rate.

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