Method Bundles

Performance-critical systems commonly optimize memory use and locality by selecting among multiple variants of a single logical operation. Algorithm developers then typically rely on ad-hoc API patterns or naming conventions to distinguish the variants. Unfortunately, this practice suffers from poor ergonomics. Users are compelled to understand the conventions and carefully consider the signatures and documentation of different variants, which creates drag on development and maintenance. Instead, we propose a language construct bundling algorithm variants having well-defined semantic relationships under a single name. This approach eliminates boilerplate, reduces cognitive overhead by consolidating APIs, and unlocks compiler optimizations.

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Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1145/3687997.3695633
Primary Topic
Logic, programming, and type systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Method Bundles

Dimitri Racordon, Dave Abrahams
Logic, programming, and type systems
article

Method Bundles

Dimitri Racordon, Dave Abrahams
article en

Abstract

Performance-critical systems commonly optimize memory use and locality by selecting among multiple variants of a single logical operation. Algorithm developers then typically rely on ad-hoc API patterns or naming conventions to distinguish the variants. Unfortunately, this practice suffers from poor ergonomics. Users are compelled to understand the conventions and carefully consider the signatures and documentation of different variants, which creates drag on development and maintenance. Instead, we propose a language construct bundling algorithm variants having well-defined semantic relationships under a single name. This approach eliminates boilerplate, reduces cognitive overhead by consolidating APIs, and unlocks compiler optimizations.

Adobe Systems (United States) (US), École Polytechnique Fédérale de Lausanne (CH)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 84%
Logic, programming, and type systems
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Method Bundles — Dimitri Racordon, Dave Abrahams · (2024) | TGRS Research Map | TGRS