A Neural Network Model for Estimation Having Reusable Components in Software Development

Software effort estimation is one of the most critical and complex task in software engineering, but it is an inevitable activity in the software development processes. Due to the inherent uncertainty in software development projects such as complex and dynamic interaction factors, change of requirements, intrinsic software complexity, pressure on standardization and lack of software data, it is unrealistic to expect very accurate effort estimation of software development processes. 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 reusability in software development effort estimation. The proposed model is based on dynamic neural network technique using back propagation algorithm which provides better accuracy for effort estimation.