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Polymorphic Types with Polynomial Sizes

Authors: Colaço, Jean-Louis; Pauget, Baptiste; Pouzet, Marc;

Polymorphic Types with Polynomial Sizes

Abstract

This article presents a compile-time analysis for tracking the size of data-structures in a statically typed and strict functional language. This information is valuable for static checking and code generation. Rather than relying on depen- dent types, we propose a type-system close to that of ML: polymorphism is used to define functions that are generic in types and sizes; both can be inferred. This approach is con- venient, in particular for a language used to program critical embedded systems, where sizes are indeed known at compile- time. By using sizes that are multivariate polynomials, we obtain a good compromise between the expressiveness of the size language and its properties (verification, inference).The article defines a minimal functional language that is sufficient to capture size constraints in types. It presents its dynamic semantics, the type system and inference algorithm. Last, we sketch some practical extensions that matter for a more realistic language.

Keywords

array programming, Type systems, [INFO] Computer Science [cs]

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
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