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Context sensitivity is essential for achieving the precision ininter-procedural static analysis. To be (fully) context sensitive, top-downanalysis needs to fully inline all statements of the callees at each callsite,leading to statement explosion. Compositional analysis, which inlines summariesof the callees, scales up but often loses precision, as it is not strictlycontext sensitive. We propose a compositional and strictly context sensitiveframework for static analysis. This framework is based on one key observation:a compositional static analysis often loses precision only on some criticalstatements that need to be analyzed context sensitively. Our approach hybridlyinlines the critical statements and the summaries of non-critical statements ofeach callee, thus avoiding the re-analysis of non-critical ones. In addition,our analysis lazily summarizes the critical statements, by stopping propagatingthe critical statements once the calling context accumulated is adequate.Hybrid Inlining can be as precise as context sensitive top-down analysis. Wehave designed and implemented a pointer analysis based on this framework. Itcan analyze large Java programs from the Dacapo benchmark suite and industry inminutes. In our evaluation, compared to context insensitive analysis, HybridInlining just brings 65% and 1% additional time overhead on Dacapo andindustrial applications respectively.

Hybrid Inlining: A Compositional and Context Sensitive Static Analysis Framework