Advances in Web Application Testing, 2010–2014

Sampath, Sreedevi; Sprenkle, Sara

doi:10.1016/bs.adcom.2015.11.006

Cited by 1 publication

(1 citation statement)

References 29 publications

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“…Web application testing proves to be a difficult task and the advent of Ajax applications has increased the complexity even further. Conventional web testing techniques [19][20][21][22][23] do not test Ajax application features like asynchronous communication, client-server parallelism, and dynamic page segment updates. These features have added the issues like forward-back page navigation, enormous state changing elements, state explosion, and unreachable states.…”

Section: Introductionmentioning

confidence: 99%

Achieving State Space Reduction in Generated Ajax Web Application State Machine

Malik¹,

Nadeem²,

Sindhu³

2022

Intelligent Automation &Amp; Soft Computing

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The testing of Ajax (Asynchronous JavaScript and XML) web applications poses novel challenges for testers because Ajax constructs dynamic web applications by using Asynchronous communication and run time Document Object Model (DOM) manipulation. Ajax involves extreme dynamism, which induces novel kind of issues like state explosion, triggering state changes and unreachable states etc. that require more demanding web-testing methods. Model based testing is amongst the effective approaches to detect faults in web applications. However, the state model generated for an Ajax application can be enormous and may be hit by state explosion problem for large number of user action based changes and for immense dynamism. Recent research has not addressed this issue comprehensively because existing techniques either apply partial reduction or compromise the effectiveness of testing. This research uses soft computing based Fuzzy C Means (FCM) clustering algorithm to generate state machine model of an Ajax web application. The focus is on devising a framework to avoid the state explosion problem. The framework prioritizes the requirements and use cases based on requirements weightage, stakeholder weightage and user session based use case frequency. FCM uses this data to reduce the state space by identifying the most pivotal usage areas. The resultant DOM mutations for only these usage areas are considered to induce the finite state machine thus avoiding the state explosion. Experimental results show that the framework controls the size of generated state machine without compromising the effectiveness of testing.

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