Early Size and Effort Estimation of Mobile Application Development

Abstract

With the increased complexity in mobile applications, many challenges and issues emerged for the software project management team to develop mobile application effectively and accurately. Effort estimation is one of the most critical issues the Software management project team faces in general, and the mobile application development team in specific. Effort estimation helps to approximate the cost required for successful software application development. The mobile application is distinct in various aspects from the traditional software and web-based applications. There is a need for a specific methodology to be followed for accurate estimation of size and efforts. This research aims to review the effectiveness of COSMIC and Machine Learning techniques in performing mobile effort estimation and propose a hybrid approach for efficient mobile effort estimation. This research work's mains represent the methodology followed to achieve the input parameters and mobile applications' efforts using a tailor-made approach. The significance of this research work is to propose a framework that will help both researchers and mobile application estimators approximate the efficient efforts precisely.

Keywords

• effort estimation
• mobile application development
• mobile effort estimation methodology
• hybrid machine learning techniques
• cpeem approaches