A Novel Approach to Software Cost Estimation Using Genetic Algorithm Classifier
Tirimula Rao Benala, S. Sumana, Avinash Anaparthi, Srivalli Namala · SSRN Electronic Journal · 2010
This paper presents a method for optimizing the software testing efficiency by using the genetic algorithm classifier. Here the datasets of certain attributes are taken as the inputs and the output i.e. persons-month(PM) is obtained. We have divided into 5 classes each as the particular range of PM. The rules are defined for each class by using the genetic algorithm. The input is matched with the rules and is segregated to respective classes. Then the neural network is used to get the accurate persons-month. By using the above procedure the estimating efficiency can be increased.