Extending Data Spatial Semantics for Scale Agnostic Programming

Fuente: arXiv
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Main Author: Mars, Jason
Format: Preprint
Published: 2025
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author Mars, Jason
author_facet Mars, Jason
contents We introduce extensions to Data Spatial Programming (DSP) that enable scale-agnostic programming for application development. Building on DSP's paradigm shift from data-to-compute to compute-to-data, we formalize additional intrinsic language constructs that abstract persistent state, multi-user contexts, multiple entry points, and cross-machine distribution for applications. By introducing a globally accessible root node and treating walkers as potential entry points, we demonstrate how programs can be written once and executed across scales, from single-user to multi-user, from local to distributed, without modification. These extensions allow developers to focus on domain logic while delegating runtime concerns of persistence, multi-user support, distribution, and API interfacing to the execution environment. Our approach makes scale-agnostic programming a natural extension of the topological semantics of DSP, allowing applications to seamlessly transition from single-user to multi-user scenarios, from ephemeral to persistent execution contexts, and from local to distributed execution environments.
format Preprint
id arxiv_https___arxiv_org_abs_2504_03109
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Extending Data Spatial Semantics for Scale Agnostic Programming
Mars, Jason
Programming Languages
Distributed, Parallel, and Cluster Computing
Multiagent Systems
Operating Systems
Software Engineering
We introduce extensions to Data Spatial Programming (DSP) that enable scale-agnostic programming for application development. Building on DSP's paradigm shift from data-to-compute to compute-to-data, we formalize additional intrinsic language constructs that abstract persistent state, multi-user contexts, multiple entry points, and cross-machine distribution for applications. By introducing a globally accessible root node and treating walkers as potential entry points, we demonstrate how programs can be written once and executed across scales, from single-user to multi-user, from local to distributed, without modification. These extensions allow developers to focus on domain logic while delegating runtime concerns of persistence, multi-user support, distribution, and API interfacing to the execution environment. Our approach makes scale-agnostic programming a natural extension of the topological semantics of DSP, allowing applications to seamlessly transition from single-user to multi-user scenarios, from ephemeral to persistent execution contexts, and from local to distributed execution environments.
title Extending Data Spatial Semantics for Scale Agnostic Programming
topic Programming Languages
Distributed, Parallel, and Cluster Computing
Multiagent Systems
Operating Systems
Software Engineering
url https://arxiv.org/abs/2504.03109