Cycle elimination for invocation graph-based context-sensitive pointer analysis

Context: Pointer analysis is an important building block of optimizing compilers and program analyzers for C language. Various methods with precision and performance trade-offs have been proposed. Among them, cycle elimination has been successfully used to improve the scalability of context-insensitive pointer analyses without losing any precision. Objective: In this article, we present a new method on context-sensitive pointer analysis with an effective application of cycle elimination. Method: To obtain similar benefits of cycle elimination for context-sensitive analysis, we propose a novel constraint-based formulation that uses sets of contexts as annotations. Our method is not based on binary decision diagram (BDD). Instead, we directly use invocation graphs to represent context sets and apply a hash-consing technique to deal with the exponential blow-up of contexts. Result: Experimental results on C programs ranging from 20,000 to 290,000 lines show that applying cycle elimination to our new formulation results in 4.5 xspeedup over the previous BDD-based approach. Conclusion: We showed that cycle elimination is an effective method for improving the scalability of context-sensitive pointer analysis.