an interprocedural data flow analysis algorithm
A new interprocedural data flow analysis algorithm is presented and analyzed. The algorithm associates with each procedure in a program information about which variables may be modified, which may be used, and which are possibly preserved by a call on the procedure, and all of it subcalls. The algorithm is sufficiently powerful to be used on recursive programs and to deal with the sharing of variables which arises through reference parameters. The algorithm is unique in that it can compute all of this information in a single pass, not requiring a prepass to compute calling relationships or sharing patterns. A lower bound for the computational complexity of gathering interprocedural data flow information is derived and the algorithm is shown to be asymptotically optimal. The algorithm has been implemented and it is practical for use even on quite large programs.
data flow analysis data flow algorithm association program informal variability use recursion sharing computation relationships pattern lower bound computational complexity optimality practical