MANDOLINE: Dynamic Slicing of Android Applications with Trace-Based Alias Analysis

Dynamic program slicing is used in a variety of tasks, including program debugging and security analysis. Building an efficient and effective dynamic slicing tool is a challenging task, especially in an Android environment, where programs are event-driven, asynchronous, and interleave code written by a developer with the code of the underlying Android platform. The user-facing nature of Android applications further complicates matters as the slicing solution has to maintain a low overhead to avoid substantial application slowdown. In this paper, we propose an accurate and efficient dynamic slicing technique for Android applications and implement it in a tool named MANDOLINE. The core idea behind our technique is to use minimal, low-overhead instrumentation followed by sophisticated, on-demand execution trace analysis for constructing a dynamic slice. We also contribute a benchmark suite of Android applications with manually constructed dynamic slices that use a faulty line of code as a slicing criterion. We evaluate MANDOLINE on that benchmark suite and show that it is substantially more accurate and efficient than the state-of-the-art dynamic slicing technique named ANDROIDSLICER.