Effort Estimation of Web Based Applications Using ERD, Use Case Point Method and Machine Learning

Abstract

Effort estimation of a web-based application is treated as the most important process before the development of the application. It is stated by many studies and researches that accurate effort estimation rate increases the success rate for developing the application. There are quite a few methodologies for estimating the effort the web-based application. Earlier the effort estimation process did not include the back-end part or the database part of the application. Since nowadays, the software are more data-centric and thus database has become such a crucial part of the software product, therefore to get more accurate estimations, the back-end part of web based application has to be taken into consideration. This paper deals with finding more accurate effort prediction of a web application with the inclusion of the back-end part of application using different techniques. In this paper, the proposed effort estimation method using the backend has been discussed and benchmarked against the current models including ML models for effort estimation.