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ZENODO
Software . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
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Aria Programming Language

Authors: Hoggard, Randy;

Aria Programming Language

Abstract

The proliferation of autonomous systems, ranging from advanced robotics to high-stakesalgorithmic trading and Artificial General Intelligence (AGI) substrates, has precipitated a crisisin systems software reliability. Traditional languages, designed in an era prioritizing executionspeed over correctness, expose critical infrastructure to non-deterministic failures and undefinedbehaviors. This paper presents a comprehensive, architectural analysis of Aria, a novel systemsprogramming language designed to enforce a "Safety Above All Else" philosophy. Through arigorous examination of the compiler source code, runtime specifications, and theoreticalunderpinnings, we dissect Aria’s radical departures from conventional language design. Weanalyze the Twisted Balanced Binary (TBB) type system, which enforces symmetric arithmeticwith embedded error sentinels to prevent silent overflow corruption. We explore the Limb-BasedIntegral Model (LBIM), a structural workaround for backend optimization instability that enablessafe post-quantum cryptography. Furthermore, we investigate the "Sentinel DiscontinuityConstraint," the "Appendage Theory" of metadata management, and the language’s dual-memorymodel (GC/Wild) utilizing the Acquire-Convert-Release (ACR) pattern. By synthesizing detailsfrom the compiler's Intermediate Representation (IR) generation and its runtime environment,this report demonstrates how Aria achieves bit-identical determinism and sticky errorpropagation, establishing a new theoretical and practical framework for high-integritycomputing.

Keywords

Programming Language, safety, ai

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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!
0
Average
Average
Average