The results obtained show that the proposed BCO based model is able to improve the accuracy of cost estimation and also outperform other models. The BCO approach generates various partial solutions and best solution is selected based on Mean Magnitude of Relative Error. The results generated by the proposed model are compared to those obtained by methods proposed in the literature using Walston-Felix, SEL, Bailey-Basil, COCOMO II and Halstead models. The proposed model validation is carried out using Interactive Voice Response software project dataset of a company. Since the accuracy of the COCOMO II stands over the cost derives and scale.

These artificial agents or bees are used to solve complex combinatorial optimization problems. improving the accuracy of one of the popular effort estimation models, COCOMO II. Eventually, both the customer and the organi- sation are interested in the cost of the project in its dol- lar value.

organization and the extent of parallelism that can be derived. To evaluate the model using ConteÕs criteria 5. fort, taking into account the resource constraints of an 4. BCO approach is a “bottom-up” approach to modeling where special kinds of artificial agents are created by analogy with bees. To t COCOMO II.2000 Model for practical data in is the calendar time it would take to accomplish the ef- a software company. Thus, it is not surprising that some of the concepts defined or used in the COCOMO model are somewhat incompatible with the software measurement theory.

The Bee Colony Optimization (BCO) is a new branch of Swarm Intelligence and has been applied successfully to various engineering disciplines. The objective of current research is applying Bee Colony Optimization (BCO) metaheuristic approach to optimize the parameters of COCOMO model for improving software cost estimation. Constructive Cost Model (COCOMO) used parameters for software effort estimation, which were calculated in 1981 by regression analysis of 63 types of project data therefore applying these parameters to current project development will not generate accurate results.

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