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Precision-preserving yet fast object-sensitive pointer analysis with partial context sensitivity
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DOI：10.1145/3360574.png)
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Abstract
En 中文
Object-sensitivity is widely used as a context abstraction for computing the points-to information context-sensitively for object-oriented languages like Java. Due to the combinatorial explosion of contexts in large programs,
k
-object-sensitive pointer analysis (under
k
-limiting), denoted
k
-obj, is scalable only for small values of
k
, where
k
⩽2 typically. A few recent solutions attempt to improve its efficiency by instructing
k
-obj to analyze only some methods in the program context-sensitively, determined heuristically by a pre-analysis. While already effective, these heuristics-based pre-analyses do not provide precision guarantees, and consequently, are limited in the efficiency gains achieved. We introduce a radically different approach, Eagle, that makes
k
-obj run significantly faster than the prior art while maintaining its precision. The novelty of Eagle is to enable
k
-obj to analyze a method with partial context-sensitivity, i.e., context-sensitively for only some of its selected variables/allocation sites. Eagle makes these selections during a lightweight pre-analysis by reasoning about context-free-language (CFL) reachability at the level of variables/objects in the program, based on a new CFL-reachability formulation of
k
-obj. We demonstrate the advances made by Eagle by comparing it with the prior art in terms of a set of popular Java benchmarks and applications.
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