Data-Flow Guided Slicing
This work addresses code optimization for Android developers by providing a fast and scalable method to reduce program size related to data leaks, though it appears incremental as it builds on existing slicing techniques.
The authors tackled the problem of reducing program code by pruning irrelevant portions for specified data-flow paths, achieving an average reduction of 36% in code size across 10,600 Android applications.
We propose a flow-insensitive analysis that prunes out portions of code which are irrelevant to a specified set of data-flow paths. Our approach is fast and scalable, in addition to being able to generate a certificate as an audit for the computed result. We have implemented our technique in a tool called DSlicer and applied it to a set of 10600 real-world Android applications. Results are conclusive, we found out that the program code can be significantly reduced by 36% on average with respect to a specified set of data leak paths.