Lazaro Clapp

GUI input generation tools for Android apps, such as Android’s Monkey, are useful for automatically producing test inputs, but these tests are generally orders of magnitude larger than necessary, making them difficult for humans to understand. We present a technique for minimizing the output of such tools. Our technique accounts for the nondeterministic behavior of mobile apps, producing small event
traces that reach a desired activity with high probability.

We propose a variant of… Show more

GUI input generation tools for Android apps, such as Android’s Monkey, are useful for automatically producing test inputs, but these tests are generally orders of magnitude larger than necessary, making them difficult for humans to understand. We present a technique for minimizing the output of such tools. Our technique accounts for the nondeterministic behavior of mobile apps, producing small event
traces that reach a desired activity with high probability.

We propose a variant of delta debugging, augmented to handle non-determinism, to solve the problem
of trace minimization. We evaluate our algorithm on two sets of commercial and open-source Android applications, showing that we can minimize large event traces reaching a particular application activity, producing traces that are, on average, less than 2% the size of the original traces. Show less

We present a technique to mine explicit information flow specifications from concrete executions. These specifications can be consumed by a static taint analysis, enabling static analysis to work even when method definitions are missing or portions of the program are too difficult to analyze statically (e.g., due to dynamic features such as reflection). We present an implementation of our technique for the Android platform. When compared to a set of manually written specifications for 309… Show more

We present a technique to mine explicit information flow specifications from concrete executions. These specifications can be consumed by a static taint analysis, enabling static analysis to work even when method definitions are missing or portions of the program are too difficult to analyze statically (e.g., due to dynamic features such as reflection). We present an implementation of our technique for the Android platform. When compared to a set of manually written specifications for 309 methods across 51 classes, our technique is able to recover 96.36% of these manual specifications and produces many more correct annotations that our manual models missed. We incorporate the generated specifications into an existing static taint analysis system, and show that they enable it to find additional true flows. Although our implementation is Android-specific, our approach is applicable to other application frameworks. Show less