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AI Summary: Proposes a neurosymbolic framework that translates natural language prompts into formal mathematical specifications, allowing for the automated verification of AI-generated code architectures.
AI Summary: Proposes a neurosymbolic framework that translates natural language prompts into formal mathematical specifications, allowing for the automated verification of AI-generated code architectures.
The rapid adoption of natural language programming ('vibe coding') has democratized software creation but introduced unprecedented levels of technical debt and architectural instability. We propose a neurosymbolic framework that bridges the gap between informal natural language intent and rigorous software engineering. Our system automatically translates high-level agentic prompts into formal specifications (e.g., TLA+, Coq) and uses SMT solvers to mathematically verify the logical consistency of the generated architecture before code execution. This approach guarantees that 'vibe-coded' applications adhere to strict security and operational constraints, effectively bringing formal verification to the masses.
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