Error Analytic Model for Web Application Reliability Improvement

N. Alaeddine and J. Tian (USA)

Keywords

Web testing, web reliability, and defect classification

Abstract

Ensuring web application quality increasingly becoming more important as Internet today is vital technology for mankind. In this paper, we introduce an analysis and classification method to improve web application quality and reliability. This technique integrates Orthogonal Defect Classification (ODC), and Markov Chain to classify as well as analyze web errors. The hierarchical Markov Chain models web usage and web errors. The constructed model is used to analyze and classify the errors guided by a set of web error attributes. The errors collected from web server logs and defect data. This technique enables viewing the errors at most used pages, most used paths and at application contexts. This proposed method helps in developing reliable web applications that benefit from the understanding of web anomalies and past issues. The results of applying our approach to a case study from the telecommunications industry are included to show its applicability and effectiveness.

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