Anomaly Detection and Quality Evaluation of Web Applications

Anomaly Detection and Quality Evaluation of Web Applications

May Haydar (Université de Montréal, Canada), Ghazwa Malak (Université de Montréal, Canada), Houari Sahraoui (Université de Montréal, Canada), Alexandre Petrenko (Centre de recherche informatique de Montréal (CRIM), Canada) and Sergiy Boroday (Centre de recherche informatique de Montréal (CRIM), Canada)
Copyright: © 2008 |Pages: 18
DOI: 10.4018/978-1-59904-847-5.ch005
OnDemand PDF Download:
$37.50

Abstract

This chapter addresses the problem of Web application quality assessment from two perspectives. First, it shows the use of model checking of properties formulated in LTL to detect anomalies in Web applications. Anomalies can be derived from standard quality principles or defined for a specific organization or application. The detection is performed on communicating automata models inferred from execution traces. Second, the chapter explains how probabilistic models (Bayesian networks) can be built and used to evaluate quality characteristics. The structure of the networks is defined by refinement of existing models, where the parameters (probabilities and probability tables) are set using expert judgment and fuzzy clustering of empirical data. The two proposed approaches are evaluated and a discussion on how they complement each other is presented.

Key Terms in this Chapter

Formal Verification: The use of formal methods to ensure that a set of properties are valid in a given system under test.

Quality: The totality of features and characteristics of a product or service that bear on its ability to satisfy stated or implied needs.

Web Analysis: The process to analyze the behavior of Web applications for the purpose of verification and validation.

Measurement: The determination of the dimensions, in whatever types of units, of an object, product, or process.

Web Application: An application providing interactive services by rendering Web resources in the form of Web pages.

GQM: A goal-driven method for developing and maintaining a meaningful measurement program that is based on three levels, goals, questions, and metrics.

Usability: A set of attributes that bear on the effort needed for use, and on the individual assessment of such use, by a stated or implied set of users (ISO/IEC 9126).

Complete Chapter List

Search this Book:
Reset