Feature Mapping and Detecting Data Inconsistencies in Cross Platform Mobile Application

Abstract

The advancement and popularity of mobile device made the developers to develop applications which are used for multiple platforms like iOS, Android etc. Every mobile platform has its special condition in essentials of tools, encoding dialects and Applications. Recently iOS and Android hybrid mobile applications dominate the application market. So as to focus for more clients, actualizing the mobile application over the multiple platforms has turned into a typical practice for mobile application developers. The developed mobile applications should provide same functionality, features and behaviors on different platforms which are user friendly. But it is difficult to make applications consistence across different platforms. The cross platform inconsistencies identified when it runs on different operating systems and causes behavioral issues (iOS/ ANDROID). newlineThe featCHECK automated technique implemented for detecting inconsistencies in hybrid/cross platform application for iOS and Android platforms. featCHECK technique has been classified into four categories for detecting inconsistencies: newline1. Repeatedly instruments and traces the application on both iOS and Android platform for specified implementation scenarios. newline2. Identifies inconsistencies from iOS and Android platform by executing matching traces. newlinexv newline3. A set of code-based has been compared with the models using and GUI-based criteria to depict any discrepancies to end with. newline4. Generates an idea of the models and highlighting the detected inconsistencies. newlinefeatCHECK can assist mobile developers in testing their applications across multiple platforms. The approach has been evaluated with a set of 25 open-source cross platform/ hybrid mobile app-pairs which indicates that featCHECK can appropriately mine inconsistencies from mobile applications of multiple platforms and conclude mappings between thecross platform applications based on dissimilar evaluation criteria, and detect inconsistencies at cross platform application and their levels of severity. newline