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Hybrid Context-Sensitivity for Points-To Analysis

January 1, 2013
RelationalAI

Context-sensitive points-to analysis is valuable for achieving high precision
with good performance.

Authors: George Kastrinis´, Yannis Smaragdakis. 2013.

In Proceedings of the 34th ACM SIGPLAN Conference on Programming Language
Design and Implementation (PLDI ‘13).

Context-sensitive points-to analysis is valuable for achieving high precision
with good performance. The standard flavors of context-sensitivity are
call-site-sensitivity (kCFA) and object-sensitivity. Combining both flavors of
context-sensitivity increases precision but at an infeasibly high cost. We show
that a selective combination of call-site- and object-sensitivity for Java
points-to analysis is highly profitable.

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Hybrid Context-Sensitivity for Points-To Analysis