On String Prioritization in Web-Based User Interface Localization

We have noticed that most of the current challenges affecting user interface localization could be easily approached if string prioritization would be made possible. In this paper, we tackle these challenges through Nimrod, a web-based internationalization tool that prioritizes user interface strings using a number of discriminative features. As a practical application, we investigate different prioritization strategies for different string categories from Wordpress, a popular open-source content management system with a large message catalog. Further, we contribute with WPLoc, a carefully annotated dataset so that others can reproduce our experiments and build upon this work. Strings in the WPLoc dataset are labeled as relevant and non-relevant, where relevant strings are in turn categorized as critical, informative, or navigational. Using state-of-the-art classifiers, we are able to retrieve strings in these categories with competitive accuracy. Nimrod and the WPLoc dataset are both publicly available for download.