Extending Data Spatial Semantics for Scale Agnostic Programming
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909564767567872 |
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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 |