X-PERT: accurate identification of cross-browser issues in web applications

  • Authors:
  • Shauvik Roy Choudhary;Mukul R. Prasad;Alessandro Orso

  • Affiliations:
  • Georgia Tech, USA;Fujitsu Labs, USA;Georgia Tech, USA

  • Venue:
  • Proceedings of the 2013 International Conference on Software Engineering
  • Year:
  • 2013

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Abstract

Due to the increasing popularity of web applications, and the number of browsers and platforms on which such applications can be executed, cross-browser incompatibilities (XBIs) are becoming a serious concern for organizations that develop web-based software. Most of the techniques for XBI detection developed to date are either manual, and thus costly and error-prone, or partial and imprecise, and thus prone to generating both false positives and false negatives. To address these limitations of existing techniques, we developed X-PERT, a new automated, precise, and comprehensive approach for XBI detection. X-PERT combines several new and existing differencing techniques and is based on our findings from an extensive study of XBIs in real-world web applications. The key strength of our approach is that it handles each aspects of a web application using the differencing technique that is best suited to accurately detect XBIs related to that aspect. Our empirical evaluation shows that X-PERT is effective in detecting real-world XBIs, improves on the state of the art, and can provide useful support to developers for the diagnosis and (eventually) elimination of XBIs.