A Dynamic Neural Network Model for Estimation in Software Development having Reusable Components

In software engineering, the most critical task is to estimate the effort involved in the project due to inevitable activities involved in the software development process. The various factors such as change of requirements, intrinsic software complexity, lack of software data etc. are responsible to expect very accurate effort estimation in the software development process. Many estimation models are used to prove accuracy but none of them have able to prove that it has accuracy in all cases of software applications. The paper focuses on the estimation of the software development process having reusable components. The proposed model is based on dynamic neural network technique using back propagation algorithm which provides better accuracy for effort estimation.