An Automated Testing Framework for Cross-Browser Visual Incompatibility Detection

Authors

  • Zhen Xu University of Alberta, Edmonton, Canada
  • James Miller University of Alberta, Edmonton, Canada

DOI:

https://doi.org/10.33633/jais.v3i1.1809

Abstract

Due to the rapid evolution of web applications and computer techniques, visual incompatibility of web pages has become a problem across different browsers and platforms influencing the functionality of the web applications. At the present, researchers have made progress to address such issues; in addition, many commercial tools have emerged as well. However, drawbacks still exist in the existing work, where fully automate testing at the system level is still not achieved. In this paper, we attempt to propose a framework to detect the cross browser visual incompatibilities automatically. Highlights of the proposed framework include template based case organization, version based automation, and similarity embedded incompatibilities identification.

References

Ali Mesbah and Mukul R. Prasad. 2011. Automated cross-browser compatibility testing. Proceedings of the 33rd International Conference on Software Engineering. ACM, 561–570.

Shauvik Roy Choudhary, Mukul R Prasad, and Alessandro Orso. 2012. Crosscheck: Combining crawling and differencing to better detect cross-browser incompatibilities in web applications. 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation. IEEE, 171–180.

Shauvik Roy Choudhary, Mukul R Prasad, and Alessandro Orso. 2013. X-PERT: accurate identification of cross-browser issues in web applications. Proceedings of the 2013 International Conference on Software Engineering. IEEE Press, 702–711.

Zhen Xu, James Miller. Estimating similarity of rich internet pages using visual information. International Journal of Web Engineering and Technology 12, no. 2 (2017): 97-119.

Ali Shahbazi and James Miller. 2014. Extended subtree: a new similarity function for tree structured data. Knowledge and Data Engineering, IEEE Transactions on 26, 4 (2014), 864–877.

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Published

2018-08-03

Issue

Vol. 3 No. 1 (2018): Journal of Applied Intelligent System

Section

Articles

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