Testing the Message Flow of Android Auto Apps

Android Auto is designed to enhance the driving experience by extending dashboards of cars with smartphones’ functionalities, among which an essential one is the message flow via notification mechanism. This paper investigates the quality of current compatible apps, and locates two main error-prone points. The study begins with manually designed black-box testing models including finite state machine and combinatorial input model according to safety requirements, and extracts testing suites from them. The tests are executed on 17 popular apps and reveal dozens of defects that might result in safety risks or inferior driving experiences. These defects are manually inspected and organized into several patterns. The experience and lessons from this empirical study are helpful to the detailed design and implementation of messaging modules.