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Cited by 916

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

A unified approach to global program optimization

Kildall, Gary A.·1973·Proceedings of the 1st annual ACM SIGACT-SIGPLAN symposium on Principles of programming languages - POPL '73

Abstract

A technique is presented for global analysis of program structure in order to perform compile time optimization of object code generated for expressions. The global expression optimization presented includes constant propagation, common subexpression elimination, elimination of redundant register load operations, and live expression analysis. A general purpose program flow analysis algorithm is developed which depends upon the existence of an "optimizing function." The algorithm is defined formally using a directed graph model of program flow structure, and is shown to be correct. Several optimizing functions are defined which, when used in conjunction with the flow analysis algorithm, provide the various forms of code optimization. The flow analysis algorithm is sufficiently general that additional functions can easily be defined for other forms of global code optimization.

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Metadata

Authors
Kildall, G. A.
Venue
Proceedings of the 1st annual ACM SIGACT-SIGPLAN symposium on Principles of programming languages - POPL '73
Publisher
ACM Press
Published
1973
Pages
194-206
OpenAlex
W2124153277
Cited by
916
References
9
FWCI
9.28
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: A unified approach to global program optimization. https://app.cochat.ai/papers/10.1145/512927.512945
The paper
Kildall, G. A. (1973). A unified approach to global program optimization. Proceedings of the 1st annual ACM SIGACT-SIGPLAN symposium on Principles of programming languages - POPL '73. https://doi.org/10.1145/512927.512945

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.