Double iterative framework for flow-sensitive interprocedural data flow analysis

Abstract

Compiler optimization, parallel processing, data flow testing, and symbolic debugging can benefit from interprocedural data flow analysis. However, the live, reaching definition, and most summary data flow problems are theoretically intractable in the interprocedural case. A method is presented that reduces the exponential time bound with the help of an algorithm that solves the problem in polynomial time. Either the resulting sets contain precise results or the missing (or additional) results do not cause any problems during their use. We also introduce the double iterative framework, where one procedure is processed at a time. The results of the intraprocedural analysis of procedures then propagates along the edges of the call multi-graph. In this way the intra and interprocedural analyses are executed alternately until there is no change in any result set. This method can be applied to any known interprocedural data flow problem. Here the algorithms for the kill, live variables, and reaching definitions problems are presented. Besides for precision, the algorithms can be used for very large programs, and since inter and intraprocedural analyses can be optimized separately, the method is fast as well.