PUMA: programmable UI-automation for large-scale dynamic analysis of mobile apps

Abstract

Mobile app ecosystems have experienced tremendous growth in the last six years. This has triggered research on dynamic analysis of performance, security, and correctness properties of the mobile apps in the ecosystem. Exploration of app execution using automated UI actions has emerged as an important tool for this research. However, existing research has largely developed analysis-specific UI automation techniques, wherein the logic for exploring app execution is intertwined with the logic for analyzing app properties. PUMA is a programmable framework that separates these two concerns. It contains a generic UI automation capability (often called a Monkey) that exposes high-level events for which users can define handlers. These handlers can flexibly direct the Monkey's exploration, and also specify app instrumentation for collecting dynamic state information or for triggering changes in the environment during app execution. Targeted towards operators of app marketplaces, PUMA incorporates mechanisms for scaling dynamic analysis to thousands of apps. We demonstrate the capabilities of PUMA by analyzing seven distinct performance, security, and correctness properties for 3,600 apps downloaded from the Google Play store.