Research
REBEE- Reusability Based Effort Estimation Technique using Dynamic Neural Network
Software Effort Estimation has been researched for over 25 years but until today no real effective model could be designed that could efficiently gauge the effort required for heterogeneous project data. Reusability factors of software development have been used to design a new effort estimation model called REBEE. This encompasses the usage of Fuzzy Logic and Dynamic Neural Networks. The experimental evaluation of the model depicts efficient effort estimation over varied project types.
An Approach for Effort Estimation having Reusable Components in Software Development
Estimation of the effort required for development has been researched for over 25 years now. Still there exists no concrete solution to estimate the development effort. Prior experience in similar type of projects is a key for business today. This paper proposes an Effort Estimation Model named REBEE based on the reusable matrices to effectively estimate the effort to be involved for development. A project is assumed to consist of multiple modules and the reusability factor of each module is considered in the technique described here. REBEE utilizes fuzzy logic and dynamic neural networks to achieve its goal. Based on the experimental evaluation discussed in this paper it is evident that this model accurately predicts the effort involved on heterogeneous project types.
