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Proceedings of the ACM on Programming Languages
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY
Data sources: Datacite
DBLP
Article . 2024
Data sources: DBLP
DBLP
Preprint . 2023
Data sources: DBLP
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Stream Types

Authors: Joseph W. Cutler; Christopher Watson; Emeka Nkurumeh; Phillip Hilliard; Harrison Goldstein; Caleb Stanford; Benjamin C. Pierce;
Abstract

We propose a rich foundational theory of typed data streams and stream transformers, motivated by two high-level goals. First, the type of a stream should be able to express complex sequential patterns of events over time. And second, it should describe the internal parallel structure of the stream, to support deterministic stream processing on parallel and distributed systems. To these ends, we introduce stream types , with operators capturing sequential composition, parallel composition, and iteration, plus a core calculus λ ST of transformers over typed streams that naturally supports a number of common streaming idioms, including punctuation, windowing, and parallel partitioning, as first-class constructions. λ ST exploits a Curry-Howardlike correspondence with an ordered variant of the Logic of Bunched Implication to program with streams compositionally and uses Brzozowski-style derivatives to enable an incremental, prefix-based operational semantics. To illustrate the programming style supported by the rich types of λ ST , we present a number of examples written in Delta, a prototype high-level language design based on λ ST .

Country
United States
Keywords

FOS: Computer and information sciences, Distributed Computing and Systems Software, Software engineering, Numerical and computational mathematics, Computer Science - Programming Languages, Information and Computing Sciences, 004, Theory of computation, Programming Languages (cs.PL)

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    influence
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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!
4
Top 10%
Average
Top 10%
Green
Published in a Diamond OA journal