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Abstract description of pointer data structures: an approach for improving the analysis and optimization of imperative programs

Editor: Charles N. Fischer Authors:

Laurie J. Hendren,

Alexandru NicolauAuthors Info & Claims

ACM Letters on Programming Languages and Systems (LOPLAS), Volume 1, Issue 3

Pages 243 - 260

https://doi.org/10.1145/151640.151644

Published: 01 September 1992 Publication History

Abstract

Even though impressive progress has been made in the area of optimizing and parallelizing array-based programs, the application of similar techniques to programs using pointer data structures has remained difficult. Unlike arrays which have a small number of well-defined properties, pointers can be used to implement a wide variety of structures which exhibit a much larger set of properties. The diversity of these structures implies that programs with pointer data structures cannot be effectively analyzed by traditional optimizing and parallelizing compilers.

In this paper we present a new approach that leads to the improved analysis and transformation of programs with recursively defined pointer data structures. Our approach is based on a mechanism for the Abstract Description of Data Structures (ADDS). ADDS is a simple extension to existing imperative languages that allows the programmer to explicitly describe the important properties of a large class of data structures. These abstract descriptions may be used by the compiler to achieve more accurate program analysis in the presence of pointers, which in turn enables and improves the application of numerous optimizing and parallelizing transformations. We present ADDS by describing various data structures; we discuss how such descriptions can be used to improve analysis and debugging; and we supply three important transformations enabled by ADDS.

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Abstract description of pointer data structures: an approach for improving the analysis and optimization of imperative programs

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Reviews

Reviewer: Benjamin Rayborn Seyfarth

The authors discuss the inherent difficulties in optimizing programs with pointer data structures and present a mechanism for augmenting the syntax for pointer variable declarations with useful descriptive information. The primary problem addressed is pointer aliasing: it is difficult or impossible for a compiler to determine whether two pointer variables might point to the same address. The underlying data structure might be a circularly linked list or an arbitrary graph in which more than one pointer might point to any node. Knowledge of pointer aliasing is critical to correct optimization. The authors propose that the “intent” of a pointer be specified when declaring a pointer variable. For instance, a pointer for a one-way linked list might be declared as “uniquely forward along X,” to indicate that the list would have no cycles and that each node has a unique pointer. The X part of the declaration is a “dimension” that can be used to help organize more complex structures, such as binary trees with some pointers going down the tree and some going up. This paper presents a useful concept for consideration during language design. The added description of pointer variables would help make a program more readable and could be critical for correct optimization. Anyone interested in language design and compiler optimization will be interested in this paper.

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Published In

cover image ACM Letters on Programming Languages and Systems

ACM Letters on Programming Languages and Systems Volume 1, Issue 3

Sept. 1992

104 pages

ISSN:1057-4514

EISSN:1557-7384

DOI:10.1145/151640

Editor:
Charles N. Fischer
Univ. of Wisconsin-Madison

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Copyright © 1992 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 1992

Published in LOPLAS Volume 1, Issue 3

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Huelsbergen L(2018)Dynamic resolution: a runtime technique for the parallelzation of modifications to directed acyclic graphsInternational Journal of Parallel Programming10.1007/BF0269988425:5(385-417)Online publication date: 27-Dec-2018
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https://dl.acm.org/doi/10.1109/ICPC.2006.20
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