AGILE PROJECT ESTIMATION BY OPTIMIZING VARIOUS FACTORS

Abstract

ABSTRACT

Software project estimation is the process of predicting the most realistic use of Cost or effort required to develop or maintain software based on incomplete, uncertain and/or noisy input. Poor estimation may be the cause of significant challenges in project management and in the software quality. Therefore, it is important to make the use of estimation models and appropriate techniques to avoid losses caused by poor estimation.

Software Project estimation in Agile has been an important and difficult task since the evolution of the software. Many formal and informal methods have been proposed for software estimation. It is important for estimation methods to generate realistic software estimates to build the trust of customers as well as team members. Unrealistic estimates are major factors for either software project failure or decreasing the quality of the software.

Agile software processes try to minimize the impact of insufficient estimation accuracy by ensuring that the most important functionality is developed first. This is achieved through a flexible development process with short iterations. However, there is still a need for accurate estimates, as these are the basis for staffing, planning, prioritization and contract negotiations.

To address the Software cost estimation related issues in case of agile software development, I will be proposing a new way to estimate SW required to develop software which is going to be built by agile methodologies. This new way incorporates Optimizing various factors through Genetic Algorithms and then applying Artificial Neural Network via Matlab on project Data sets which can be helpful to increase the accuracy of Software estimation in Agile Projects.