Precision-preserving yet fast object-sensitive pointer analysis with partial context sensitivity

doi:10.1145/3360574

Precision-preserving yet fast object-sensitive pointer analysis with partial context sensitivity

2019-10-10

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DOI：10.1145/3360574

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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.

Precision-preserving yet fast object-sensitive pointer analysis with partial context sensitivity

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