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Software estimation accuracy is one of the most difficult tasks for software developers. Defining the project estimated cost, duration and maintenance effort early in the development life cycle is greatest challenge to be achieved for software projects. Formal effort estimation models, like COnstructive COst MOdel (COCOMO) are limited by their inability to manage uncertainties and impression in software projects early in the project development cycle. A software effort estimation model which adopts a binary genetic algorithm technique provides a solution to adjust the uncertain and vague properties of software effort drivers. In this paper, COCOMO is used as algorithmic model and an attempt is being made to validate the soundness of genetic algorithm technique using NASA project data.
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