An optimal algorithm for the construction of the system dependence graph

Abstract

Program slicing can be used to aid in a variety of software maintenance activities including code understanding, code testing, debugging, and program reengineering. Program slicing (as well as other program analysis functions including forward slicing) can be efficiently performed on an internal program representation called a system dependence graph (SDG). The construction of the SDG depends primarily on the calculation of the transitive dependences which in turn depends in the calculation of the data dependences. In this paper we demonstrate the correctness and the optimality (with respect to the number of iterations required) of our method of calculating the transitive data dependences. We make a worst-case analysis of our algorithm, and find that is faster than the Horwitz, Reps, and Binkley (HRB) algorithm, and comparable to the Reps, Horwitz, Sagiv, and Rosay (RHSR) algorithm. Furthermore, our method requires neither the (explicit) calculation of the GMOD and GREF sets nor the construction of a linkage grammar and the corresponding subordinate characteristic graphs of the linkage grammar’s non-terminals. Unlike both the HRB and RHSR algorithms, our algorithm treats recursive procedures separately, permitting a faster (linear time) solution of non-recursive procedures. Additionally, a beneficial side effect of this method is that it provides us with a new method for performing interprocedural, flow-sensitive data flow analysis.