Recognition of Cross Browser Inconsistency by crawling and comparing extracted attributes

Patidar, Chandra Prakash; Sharma, Meera; Sharda, Varsha

doi:10.9790/9622-0707045761

Cited by 3 publications

(3 citation statements)

References 7 publications

(6 reference statements)

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“…So we were not able to find the solution for running the webpage/application on a different browser (other than Firefox). Other related tools in this field include [10]: 1) Carejax: A tool built around Crawljax, which is named Carejax, a combination of Careweb and Crawljax. Carejax will provide the foundation for crawling.…”

Section: )Websphinxmentioning

confidence: 99%

Mutual Browser Conflicts Disclosure

Patidar*,

Sharma

2019

IJRTE

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In today’s world everything is becoming web dependent, and due to the advances made in web technologies, web developers have to face various challenges. Every web application before being deployed goes through various phases which may look different on different browsers. It becomes difficult to identify correct web page when it gives differences across different browsers. The web pages may give significant differences and it is known as cross-browser inconsistency. A technology that has gained a prominent position known as AJAX (Asynchronous JavaScript and XML), in which the combination of JavaScript and Document Object Model (DOM) manipulation, along with asynchronous server communication is used to achieve a high level of user interactivity. With this change in developing web applications comes a whole set of new challenges, One way to address these challenges is through the use of a crawler that can automatically walk through different states of a highly dynamic AJAX site and create a model of the navigational paths and states. Identifying these conflicts manually is a laborious task. Mutual browser conflict disclosure presents a mechanism to identify conflicts.

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Section: )Websphinxmentioning

confidence: 99%

Mutual Browser Conflicts Disclosure

Patidar*,

Sharma

2019

IJRTE

Self Cite

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“…All approaches identified by the review to execute this task propose building a navigation/interaction model for the webpage, similar to a finite state machine graph [3,4,8,[19][20][21][22][23], then comparing these models as rendered by different browsers, using a graph isomorphism algorithm strategy. According to our framework, four technical approaches were used for generating these models: Crawljax [4,8], Webmate [3,22,23], Record'n'play [19,20], and WebSPHINX [24].…”

Section: Computer-visionmentioning

confidence: 99%

Towards Cross-browser Incompatibilities Detection: Asystematic Literature Review

Watanabe¹,

Paes²,

Silva³

2019

IJSEA

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The term Cross Browser Incompatibilities (XBI) stands for compatibility issues which can be observed while rendering a web application in different browsers, such as: Microsoft Edge, Mozilla Firefox, Google Chrome, among others. In order to detect Cross-Browser Incompatibilities-XBIs, Web developers rely on manual inspection of every web page of their applications, rendering them in various configuration environments (considering multiple OS platforms and browser versions). These manual inspections are error-prone and increase the cost of the Web engineering process. This paper has the goal of identifying techniques for automatic XBI detection, conducting a Systematic Literature Review (SLR) with focus on studies which report XBI automatic detection strategies. The selected studies were compared according to the different technological solutions they implemented and were used to elaborate a XBI detection framework which can organize and classify the state-of-the-art techniques and may be used to guide future research activities about this topic. Lab 2. These tools automatically generate screenshots of a web application as rendered by multiple browsers. However, even though they make the process of identifying XBIs easier, developers still have to rely on manual inspection of the screenshots. According to Choudhary et al., XBIs can be classified in two groups [1]: Layout Issues: caused by differences in how web browsers initially render a webpage; this type of XBI is immediately visible to the user, appearing as different positioning, size, visibility or general appearance of elements of a webpage; and

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“…For system quality evaluating, it is based on (12) international standard features and important quality performance measurements publically adopted in the evaluation of eservices which are security, reliability, accuracy, efficiency, flexibility, availability, transparency, satisfaction, facility, maintainability, performance speed as well as functional & usability aspects [11,12] that illustrated in Fig. (4) and Fig.…”

Section: System Testing and Evaluatingmentioning

confidence: 99%

An Electronic Registration for Undergraduate Students with Department Selection Based on Artificial Neural Network

Qader¹

2018

KUJSS

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Recognition of Cross Browser Inconsistency by crawling and comparing extracted attributes

Cited by 3 publications

References 7 publications

Mutual Browser Conflicts Disclosure

Mutual Browser Conflicts Disclosure

Towards Cross-browser Incompatibilities Detection: Asystematic Literature Review

An Electronic Registration for Undergraduate Students with Department Selection Based on Artificial Neural Network

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