Effective Automated Repair Of Internationalization Presentation Failures In Web Applications Using Style Similarity Clustering And Search-Based Techniques

Companies often employ (i18n) frameworks to provide translated text and localized media content on their websites in order to effectively communicate with a global audience. However, the varying lengths of text from different languages can cause undesired distortions in the layout of a web page. Such distortions, called Internationalization Presentation Failures (IPFs), can negatively affect the aesthetics or usability of the website. Most of the existing automated techniques developed for assisting repair of IPFs either produce fixes that are likely to significantly reduce the legibility and attractiveness of the pages or are limited to only detecting IPFs, with the actual repair itself remaining a labour intensive manual task. To address this problem, we propose a search-based technique for automatically repairing IPFs in web applications, while ensuring a legible and attractive page. The empirical evaluation of our approach reported that our approach was able to successfully resolve 94% of the detected IPFs for 46 real-world web pages. In a user study, participants rated the visual quality of our fixes significantly higher than the unfixed versions and also considered the repairs generated by our approach to be notably more legible and visually appealing than the repairs generated by existing techniques.