Precise interprocedural analysis using random interpretation

We describe a unified framework for random interpretation that generalizes previous randomized intraprocedural analyses, and also extends naturally to efficient interprocedural analyses. There is no such natural extension known for deterministic algorithms. We present a general technique for extending any intraprocedural random interpreter to perform a context-sensitive interprocedural analysis with only polynomial increase in running time. This technique involves computing random summaries of procedures, which are complete and probabilistically sound. As an instantiation of this general technique, we obtain the first polynomial-time randomized algorithm that discovers all linear relationships interprocedurally in a linear program. We also obtain the first polynomial-time randomized algorithm for precise interprocedural value numbering over a program with unary uninterpreted functions. We present experimental evidence that quantifies the precision and relative speed of the analysis fo...

• Type: Conference
• Year: 2005
• Where: POPL
• Authors: Sumit Gulwani, George C. Necula
• Keywords: Conservative Theoretical Bounds, NASA Grant NNA04CI57A, Polynomial-time Randomized Algorithm, POPL 2005, Programming Languages