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10 - Semantics of program representation graphs

Published online by Cambridge University Press:  06 August 2010

G. Ramalingam
Affiliation:
Microsoft Research India; Bangalore, India
Thomas Reps
Affiliation:
University of Wisconsin; Madison, WI; USA
Yves Bertot
Affiliation:
INRIA-Sophia Antipolis, France
Gérard Huet
Affiliation:
Institut National de Recherche en Informatique et en Automatique (INRIA), Rocquencourt
Jean-Jacques Lévy
Affiliation:
Institut National de Recherche en Informatique et en Automatique (INRIA), Rocquencourt
Gordon Plotkin
Affiliation:
University of Edinburgh
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Summary

Abstract

Program representation graphs (PRGs) are an intermediate representation for programs. (They are closely related to program dependence graphs.) In this paper, we develop a mathematical semantics for PRGs that, inspired by Kahn's semantics for a parallel programming language, interprets PRGs as dataflow graphs. We also study the relationship between this semantics and the standard operational semantics of programs. We show that (i) the semantics of PRGs is more defined than the standard operational semantics, and (ii) for states on which a program terminates normally, the PRG semantics is identical to the standard operational semantics.

Introduction

In this paper, we develop a mathematical semantics for program representation graphs (PRGs) and study its relationship to a standard (operational) semantics of programs. Program representation graphs are an intermediate representation of programs, introduced by Yang et al. in an algorithm for detecting program components that exhibit identical execution behaviors. They combine features of static-single-assignment forms (SSA forms) and program dependence graphs (PDGs) (See Fig. 10.1 for an example program and its PRG.) PRGs have also been used in an algorithm for merging program variants.

Program dependence graphs have been used as an intermediate program representation in various applications such as vectorization, parallelization, and merging program variants. A number of variants of the PDG have been used as the basis for efficient program analysis by optimizing compilers as well as other tools.

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