we have explored so far based on the AndroZoo apps and their meta-data that we pre-compute for facilitating high-level analyses. In a nutshell, the implications on mining Android apps are mainly located in three dimensions: (1) Code analysis; (2) App evolution analysis; and (3) Malware analysis; We now detail those research dimensions respectively.

![Overview of Our Research Dimensions.[]{data-label="fig:overview"}](resources/fig_overview.pdf){width="0.8\linewidth"}

Code Analysis
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**ICC-Aware Analysis.** Since Android apps can leak sensitive information carelessly or maliciously and malicious apps manipulate significantly more ICCs than benign apps, we propose a static analysis approach named IccTA to detect privacy leaks crossing Android components, and crossing apps with the help of ApkCombiner [@li2015apkcombiner]. Unlike state-of-the-art approaches, which mainly detect privacy leaks within single component, IccTA propagates context information among components to support inter-component communication (ICC) analysis [@li2015iccta; @li2014know].

IccTA applies a code instrumentation based approach, i.e., change the code before analyzing, in order to make the ICC analysis reusable to existing intra-component analyzers. Listing \[code:example\_icc\] illustrates a code snippet showing an ICC-based privacy leak. The device id, considered as sensitive information, is obtained and stored into an Intent object (lines 8-10) in Activity1. Then, an ICC method *startActivity* is called, which switches the current execution from 