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Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
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Odysseus: A Zero-Data Deterministic Meta-Compiler for Natural Language to Standalone Executable Synthesis

Authors: Emre, Sev;

Odysseus: A Zero-Data Deterministic Meta-Compiler for Natural Language to Standalone Executable Synthesis

Abstract

The current paradigm of artificial intelligence in software generation relies heavily on stochastic large language models (LLMs) that require massive cloud computing infrastructure, high latency, and continuous data transmission. This paper introduces Odysseus, a zero-data, edge-native meta-compiler that translates natural language into fully functional, deterministic web applications without external API calls or cloud dependencies. Utilizing a local hash-based vector space, Subject-Predicate-Object (SPO) extraction, and a stateful Co-Pilot interface, Odysseus dynamically constructs an Abstract Syntax Tree (AST). The system synthesizes complex relational databases, Role-Based Access Control (RBAC) matrices, and event-driven triggers within the browser. Furthermore, it employs a Longest Increasing Subsequence (LIS) optimized Virtual DOM reconciliation algorithm for high-performance rendering and a Runtime Bundler to export self-contained, executable HTML applications with local persistence. This paper outlines the architectural framework, mathematical models, and edge-case resolutions that establish Odysseus as a paradigm-shifting tool for decentralized software generation.

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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
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