{"title":"X-PERT:准确识别web应用程序中的跨浏览器问题","authors":"Shauvik Roy Choudhary, M. Prasad, A. Orso","doi":"10.1109/ICSE.2013.6606616","DOIUrl":null,"url":null,"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.","PeriodicalId":322423,"journal":{"name":"2013 35th International Conference on Software Engineering (ICSE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"114","resultStr":"{\"title\":\"X-PERT: Accurate identification of cross-browser issues in web applications\",\"authors\":\"Shauvik Roy Choudhary, M. Prasad, A. Orso\",\"doi\":\"10.1109/ICSE.2013.6606616\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":322423,\"journal\":{\"name\":\"2013 35th International Conference on Software Engineering (ICSE)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"114\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 35th International Conference on Software Engineering (ICSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSE.2013.6606616\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 35th International Conference on Software Engineering (ICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE.2013.6606616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
X-PERT: Accurate identification of cross-browser issues in web applications
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.