MAINTAINABILITY AND QUALITY ANALYSIS OF WEB APPLICATION

Abstract

The economy globalisation together with the need of new enterprise strategies has enormously promoted the development of web applications. Reverse engineering and reengineering methods, techniques and tools have proved useful to support the post delivery lifecycle activities of traditional software systems, such as maintenance, evolution, and migration. While considering the maintenance of web application reengineering of web application has been taken the most influential part of maintenance. Maintenance and reengineering terms are closely coupled with each other. The problem of reengineering web applications is addressed in the thesis which presents STAR paradigms to define and implement a reengineering process that involves web applications and supporting tools. The research represents approaches of reengineering in web that how reengineering process can be carried out to evolution activities in legacy system as well as proposed the V model for reengineering process. The study presents the need of the technologies and approaches for building new web-services from existing web applications. The analysis of quantitative measure of large set of websites plays a significant role in evaluating the quality of websites. The study, computes different metrics using a tool developed in MATLAB. Website quality prediction is developed using statistical and some machine learning methods. The work has been validated using dataset collected from webby awards web site. The results are analysed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results show that the model predicted using the random forest and Bayes Net methods outperformed over all the other models. Hence, based on these results it is reasonable to claim that quality models have a significant relevance with design metrics and the machine learning methods have a comparable performance with statistical methods. Univariate analysis results provide an empirical view for website design guidance and suggest which metrics are more important for website development.