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World age in Julia: optimizing method dispatch in the presence of eval

Authors:

Julia Belyakova,

Benjamin Chung,

Jan VitekAuthors Info & Claims

Proceedings of the ACM on Programming Languages, Volume 4, Issue OOPSLA

Article No.: 207, Pages 1 - 26

https://doi.org/10.1145/3428275

Published: 13 November 2020 Publication History

Abstract

Dynamic programming languages face semantic and performance challenges in the presence of features, such as eval, that can inject new code into a running program. The Julia programming language introduces the novel concept of world age to insulate optimized code from one of the most disruptive side-effects of eval: changes to the definition of an existing function. This paper provides the first formal semantics of world age in a core calculus named juliette, and shows how world age enables compiler optimizations, such as inlining, in the presence of eval. While Julia also provides programmers with the means to bypass world age, we found that this mechanism is not used extensively: a static analysis of over 4,000 registered Julia packages shows that only 4-9% of packages bypass world age. This suggests that Julia's semantics aligns with programmer expectations.

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Dynamic programming languages face semantic and performance challenges in the presence of features, such as eval, that can inject new code into a running program. The Julia programming language introduces the novel concept of world age to insulate optimized code from one of the most disruptive side-effects of eval: changes to the definition of an existing function. This paper provides the first formal semantics of world age in a core calculus named juliette, and shows how world age enables compiler optimizations, such as inlining, in the presence of eval. While Julia also provides programmers with the means to bypass world age, we found that this mechanism is not used extensively: a static analysis of over 4,000 registered Julia packages shows that only 4-9% of packages bypass world age. This suggests that Julia's semantics aligns with programmer expectations.

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References

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Cited By

Rahman ABose DShakya RPandita R(2023)Come for syntax, stay for speed, understand defects: an empirical study of defects in Julia programsEmpirical Software Engineering10.1007/s10664-023-10328-528:4Online publication date: 14-Jun-2023
https://dl.acm.org/doi/10.1007/s10664-023-10328-5
Cheli A(2021)Metatheory.jl: Fast and Elegant Algebraic Computation in Julia with Extensible Equality SaturationJournal of Open Source Software10.21105/joss.030786:59(3078)Online publication date: Mar-2021
https://doi.org/10.21105/joss.03078
Pelenitsyn ABelyakova JChung BTate RVitek J(2021)Type stability in Julia: avoiding performance pathologies in JIT compilationProceedings of the ACM on Programming Languages10.1145/34855275:OOPSLA(1-26)Online publication date: 15-Oct-2021
https://dl.acm.org/doi/10.1145/3485527
Show More Cited By

Index Terms

World age in Julia: optimizing method dispatch in the presence of eval
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Just-in-time compilers
    2. General programming languages
      1. Language features
      2. Language types
        Multiparadigm languages

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cover image Proceedings of the ACM on Programming Languages

Proceedings of the ACM on Programming Languages Volume 4, Issue OOPSLA

November 2020

3108 pages

EISSN:2475-1421

DOI:10.1145/3436718

Issue’s Table of Contents

Copyright © 2020 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 November 2020

Published in PACMPL Volume 4, Issue OOPSLA

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Czech Operational Programme Research, Development, and Education

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Cited By

Rahman ABose DShakya RPandita R(2023)Come for syntax, stay for speed, understand defects: an empirical study of defects in Julia programsEmpirical Software Engineering10.1007/s10664-023-10328-528:4Online publication date: 14-Jun-2023
https://dl.acm.org/doi/10.1007/s10664-023-10328-5
Cheli A(2021)Metatheory.jl: Fast and Elegant Algebraic Computation in Julia with Extensible Equality SaturationJournal of Open Source Software10.21105/joss.030786:59(3078)Online publication date: Mar-2021
https://doi.org/10.21105/joss.03078
Pelenitsyn ABelyakova JChung BTate RVitek J(2021)Type stability in Julia: avoiding performance pathologies in JIT compilationProceedings of the ACM on Programming Languages10.1145/34855275:OOPSLA(1-26)Online publication date: 15-Oct-2021
https://dl.acm.org/doi/10.1145/3485527
Goel ADonat-Bouillud PKřikava FKirsch CVitek J(2021)What we eval in the shadows: a large-scale study of eval in R programsProceedings of the ACM on Programming Languages10.1145/34855025:OOPSLA(1-23)Online publication date: 15-Oct-2021
https://dl.acm.org/doi/10.1145/3485502

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