A Real-World, Hybrid Event Sequence Generation Framework for Android Apps

Authors

Jun Sun, University of Nebraska-LincolnFollow

First Advisor

Witawas Srisa-an

Second Advisor

Hamid Bagheri

Date of this Version

Summer 8-2021

Citation

S. Jun, S.Witawas, B.Hamid. A Real-World, Hybrid Event Sequence Generation Framework for Android Apps.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Computer Science, Under the Supervision of Professors Witawas Srisa-an and Hamid Bagheri. Lincoln, Nebraska: August, 2021

Copyright © 2021 Jun Sun

Abstract

Generating meaningful inputs for Android apps is still a challenging issue that needs more research. Past research efforts have shown that random test generation is still an effective means to exercise User-Interface (UI) events to achieve high code coverage. At the same time, heuristic search approaches can effectively reach specified code targets. Our investigation shows that these approaches alone are insufficient to generate inputs that can exercise specific code locations in complex Android applications.

This thesis introduces a hybrid approach that combines two different input generation techniques--heuristic search based on genetic algorithm and random instigation of UI events, to reach targets hidden deep in a code-base. We apply our approach to conduct dynamic analysis to verify the static analysis results produced by \textsc{GAINDroid}, a platform incompatibility detection for Android. Our result indicates that the hybrid approach can generate inputs that reach significantly more targets than those produced by random or genetic algorithm approach individually.

Adviser: Witawas Srisa-an and Hamid Bagheri