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.
S. R. Choudhary, M. R. Prasad and A. Orso REF find that, 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.
X-PERT: accurate identification of cross-browser issues in web applications
ICSE '13
Computer Science