TL;DR
This paper introduces DSlicer, a fast and scalable flow-insensitive analysis tool that prunes irrelevant code based on data-flow paths, significantly reducing code size in real-world Android apps.
Contribution
The paper presents a novel flow-insensitive analysis method with certification capability, implemented in DSlicer, for effective code reduction based on data-flow paths.
Findings
Average code reduction of 36% in Android apps
Method is fast and scalable for large codebases
Provides a certification for the analysis results
Abstract
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.
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Software Testing and Debugging Techniques · Security and Verification in Computing