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Precise and scalable context-sensitive pointer analysis via value flow graph

Lian Li, Cristina Cifuentes, Nathan Keynes

Abstract

In this paper, we propose a novel method for context-sensitive pointer analysis using the value flow graph (VFG) formulation. We achieve context-sensitivity by simultaneously applying function cloning and computing context-free language reachability (CFL-reachability) in a novel way. In contrast to existing clone-based and CFL-based approaches, flow-sensitivity is easily integrated in our approach by using a flow-sensitive VFG where each value flow edge is computed in a flow-sensitive manner. We apply context-sensitivity to both local variables and heap objects and propose a new approximation for heap cloning.

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