We present an interprocedural generalization of the well-known (intraprocedural) Coincidence Theorem of Kam and Ullman, which provides a sufficient condition for the equivalence of the meet over all paths (MOP ) solution and the maximal fixed point (MFP ) solution to a data flow analysis problem. This generalization covers arbitrary imperative programs with recursive procedures, global and local variables, and formal value parameters. In the absence of procedures, it reduces to the classical intraprocedural version. In particular, our stack-based approach generalizes the coincidence theorems of Barth and Sharir/Pnueli for the same setup, which do not properly deal with local variables of recursive procedures. 1 Motivation Data flow analysis is a classical method for the static analysis of programs that supports the generation of efficient object code by "optimizing" compilers (cf. [He, MJ]). For imperative languages, it provides information about the program states that may occur at s...

this article, the classical application of DFA. In this context, designers of a DFA are typically faced with the problem of how to construct an algorithm that determines the set of program points of an argument program which satisfy a certain property of interest. Though this problem has been studied in detail for the intraprocedural case, the construction of interprocedural analyses is still