Creating accurate privacy nutrition labels through cross-platform code annotation

Privacy awareness has led to the introduction of mandatory privacy nutrition labels in the Apple & Google mobile app stores. These labels aim to better inform users of the apps’ data practices. However, these self reported labels have been found to be inaccurate. In response to this, this thesis presents Chai, an IDE plugin for React Native projects. Developers can use Chai to automatically find areas in their codebase which might be accessing or transmitting user data. Chai aims to assist cross-platform app developers to create accurate privacy nutrition labels.