En jämförelseanalys av Wasm-prestanda för olika programmeringsparadigmer

WebAssembly is an increasingly popular compilation target for high-performance applications across diverse environments, including web, cloud, and Internet of Things platforms. While its language-agnostic design enables support for a wide array of programming languages, the performance implications of different programming paradigms within the Wasm context remain underexplored. This study investigates the extent to which programming paradigms, namely imperative, object-oriented, and functional, influence runtime performance when targeting Wasm. Using a curated subset of benchmarks from the Computer Language Benchmarks Game, implementations were developed in representative languages for each paradigm and evaluated in both native and Wasm environments. The results reveal that while native execution consistently outperforms Wasm, the magnitude of performance degradation varies significantly across paradigms. Imperative languages exhibited the smallest slowdowns, suggesting better alignment with current Wasm compilation and runtime models. However, the analysis highlights that compiler maturity and consistency between native and Wasm toolchains play a more decisive role than paradigm alone. Languages that used the same compiler backend for both environments achieved noticeably better performance. These findings emphasise the importance of robust compiler support in maximising Wasm efficiency and provide guidance for developers and compiler designers targeting Wasm. As a rapidly evolving technology, Wasm tooling and compiler support are still in early development. The disparities observed in this study are therefore subject to change in the future.

Publication Details

Journal
KTH Publication Database DiVA (KTH Royal Institute of Technology)
Published
2025-01-01
Primary Topic
Logic, programming, and type systems
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article
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article

En jämförelseanalys av Wasm-prestanda för olika programmeringsparadigmer

KTH Publication Database DiVA (KTH Royal Institute of Technology)
Logic, programming, and type systems
article

En jämförelseanalys av Wasm-prestanda för olika programmeringsparadigmer

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Abstract

WebAssembly is an increasingly popular compilation target for high-performance applications across diverse environments, including web, cloud, and Internet of Things platforms. While its language-agnostic design enables support for a wide array of programming languages, the performance implications of different programming paradigms within the Wasm context remain underexplored. This study investigates the extent to which programming paradigms, namely imperative, object-oriented, and functional, influence runtime performance when targeting Wasm. Using a curated subset of benchmarks from the Computer Language Benchmarks Game, implementations were developed in representative languages for each paradigm and evaluated in both native and Wasm environments. The results reveal that while native execution consistently outperforms Wasm, the magnitude of performance degradation varies significantly across paradigms. Imperative languages exhibited the smallest slowdowns, suggesting better alignment with current Wasm compilation and runtime models. However, the analysis highlights that compiler maturity and consistency between native and Wasm toolchains play a more decisive role than paradigm alone. Languages that used the same compiler backend for both environments achieved noticeably better performance. These findings emphasise the importance of robust compiler support in maximising Wasm efficiency and provide guidance for developers and compiler designers targeting Wasm. As a rapidly evolving technology, Wasm tooling and compiler support are still in early development. The disparities observed in this study are therefore subject to change in the future.

KTH Publication Database DiVA (KTH Royal Institute of Technology)
Openalex Percentile: Top 72%
Logic, programming, and type systems
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En jämförelseanalys av Wasm-prestanda för olika programmeringsparadigmer · KTH Publication Database DiVA (KTH Royal Institute of Technology) (2025) | TGRS Research Map | TGRS