research-article

Polyvariant flow analysis with higher-ranked polymorphic types and higher-order effect operators

Authors:

Stefan Holdermans,

Jurriaan HageAuthors Info & Claims

ICFP '10: Proceedings of the 15th ACM SIGPLAN international conference on Functional programming

Pages 63 - 74

https://doi.org/10.1145/1863543.1863554

Published: 27 September 2010 Publication History

Abstract

We present a type and effect system for flow analysis that makes essential use of higher-ranked polymorphism. We show that, for higher-order functions, the expressiveness of higher-ranked types enables us to improve on the precision of conventional let-polymorphic analyses. Modularity and decidability of the analysis are guaranteed by making the analysis of each program parametric in the analyses of its inputs; in particular, we have that higher-order functions give rise to higher-order operations on effects. As flow typing is archetypical to a whole class of type and effect systems, our approach can be used to boost the precision of a wide range of type-based program analyses for higher-order languages.

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Cited By

Thorand FHage J(2020)Higher-Ranked Annotation Polymorphic Dependency AnalysisProgramming Languages and Systems10.1007/978-3-030-44914-8_24(656-683)Online publication date: 27-Apr-2020
https://dl.acm.org/doi/10.1007/978-3-030-44914-8_24
GILRAY TADAMS MMIGHT M(2018)Abstract allocation as a unified approach to polyvariance in control-flow analysesJournal of Functional Programming10.1017/S095679681800013828Online publication date: 1-Aug-2018
https://doi.org/10.1017/S0956796818000138
Verstoep HHage JAsai KSagonas K(2015)Polyvariant Cardinality Analysis for Non-strict Higher-order Functional LanguagesProceedings of the 2015 Workshop on Partial Evaluation and Program Manipulation10.1145/2678015.2682536(139-142)Online publication date: 13-Jan-2015
https://dl.acm.org/doi/10.1145/2678015.2682536
Show More Cited By

Index Terms

Polyvariant flow analysis with higher-ranked polymorphic types and higher-order effect operators
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language features
        Polymorphism
2. Theory of computation
  1. Semantics and reasoning

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cover image ACM Conferences

ICFP '10: Proceedings of the 15th ACM SIGPLAN international conference on Functional programming

September 2010

398 pages

ISBN:9781605587943

DOI:10.1145/1863543

General Chair:
Paul Hudak
Yale University, USA
,
Program Chair:
Stephanie Weirich
University of Pennsylvania, USA

ACM SIGPLAN Notices Volume 45, Issue 9
ICFP '10
September 2010
382 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/1932681
Issue’s Table of Contents

Copyright © 2010 ACM.

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Published: 27 September 2010

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ICFP '10: ACM SIGPLAN International Conference on Functional Programming

September 27 - 29, 2010

Maryland, Baltimore, USA

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Overall Acceptance Rate 333 of 1,064 submissions, 31%

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Cited By

Thorand FHage J(2020)Higher-Ranked Annotation Polymorphic Dependency AnalysisProgramming Languages and Systems10.1007/978-3-030-44914-8_24(656-683)Online publication date: 27-Apr-2020
https://dl.acm.org/doi/10.1007/978-3-030-44914-8_24
GILRAY TADAMS MMIGHT M(2018)Abstract allocation as a unified approach to polyvariance in control-flow analysesJournal of Functional Programming10.1017/S095679681800013828Online publication date: 1-Aug-2018
https://doi.org/10.1017/S0956796818000138
Verstoep HHage JAsai KSagonas K(2015)Polyvariant Cardinality Analysis for Non-strict Higher-order Functional LanguagesProceedings of the 2015 Workshop on Partial Evaluation and Program Manipulation10.1145/2678015.2682536(139-142)Online publication date: 13-Jan-2015
https://dl.acm.org/doi/10.1145/2678015.2682536
Hage JVermeer BVerburg G(2013)Research paperProceedings of the 3rd Computer Science Education Research Conference on Computer Science Education Research10.5555/2541917.2541919(19-30)Online publication date: 4-Apr-2013
https://dl.acm.org/doi/10.5555/2541917.2541919
Gilray TAdams MMight M(2016)Allocation characterizes polyvariance: a unified methodology for polyvariant control-flow analysisACM SIGPLAN Notices10.1145/3022670.295193651:9(407-420)Online publication date: 4-Sep-2016
https://dl.acm.org/doi/10.1145/3022670.2951936
Gilray TAdams MMight MGarrigue JKeller GSumii E(2016)Allocation characterizes polyvariance: a unified methodology for polyvariant control-flow analysisProceedings of the 21st ACM SIGPLAN International Conference on Functional Programming10.1145/2951913.2951936(407-420)Online publication date: 4-Sep-2016
https://dl.acm.org/doi/10.1145/2951913.2951936
Wang YAn HLiu ZLi LYu LZhen Y(2015)Speculative Parallelism Characterization Profiling in General Purpose Computing ApplicationsJournal of Computing Science and Engineering10.5626/JCSE.2015.9.1.209:1(20-28)Online publication date: 30-Mar-2015
https://doi.org/10.5626/JCSE.2015.9.1.20

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