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Deterministic code generation and auditing research — Bounded entropy, Cortex neural-symbolic programming, and AI-Verify static analysis. CC BY 4.0.

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Deterministic Coding

Open Interface Engineering, Inc. (openIE)

Research into deterministic code generation and auditing — replacing probabilistic AI inference with mathematically grounded verification and bounded-entropy generation.

Whitepapers

1. Bounded Entropy in Formal Languages

A Mathematical Foundation for Deterministic Code Generation

Demonstrates that programming languages, as formally bounded systems, exhibit predictable entropy that enables deterministic code generation without reliance on LLMs for the majority of tasks. Introduces Constraint Stacking and a six-layer lookup-first architecture achieving 96%+ resolution through deterministic retrieval.

2. Deterministic Code Auditing for Production-Ready Software

A Polyglot Static Analysis System with Fruition Scoring

Presents AI-Verify, a deterministic code auditing system using tree-sitter parsing across 15 programming languages. Introduces the Fruition Score for quantifying code completeness. 94.7% precision in detecting incomplete code, <100ms per file.

3. Cortex: Neural-Symbolic Programming for Energy-Efficient Code Execution

A Unified Language for Polyglot Code Lifting with Continuous Program State Representation

Presents Cortex, a neural-symbolic programming language that unifies code from 21 languages into a single intermediate representation, tracks program state via Mamba-style State Space Models, and executes with multi-backend optimization. Achieves 35-100x energy savings versus generative approaches.

Author

David Jean Charlot, PhD Open Interface Engineering, Inc. (openIE) University of California, Santa Barbara (UCSB)

License

This work is licensed under CC BY 4.0 | Open Access Research

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Deterministic code generation and auditing research — Bounded entropy, Cortex neural-symbolic programming, and AI-Verify static analysis. CC BY 4.0.

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