Nunki Harmonia

Research Papers

• Functional Safety for Language Models

  Michael K Johnston

  Nunki Harmonia

  11 February 2026

  Large language models (LLMs) are increasingly used for document and code editing, yet standard approaches typically lack formal assurances about the scope, structure, or side effects of their modifications. We introduce Functional Safety, a hierarchy-aware editing architecture that formalizes LLM-driven edits as typed plans over explicit hierarchies with deterministic execution. A stochastic planning stage operates on an explicit hierarchical representation and emits a structured plan of typed operations that separate structural reorganization from bounded content generation. We analyze each step with two footprints: a structural footprint (nodes whose relations may change) and a payload footprint (nodes whose local content may change), and the guarantees are scoped per step. Execution is performed by a deterministic, structure-constrained component that enforces locality, guards protected regions, preserves byte-for-byte payload outside each step's payload footprint, and confines structural changes to each step's structural footprint under the stated assumptions. We formalize the architecture, specify its invariants, and prove Deterministic Safety and Conditional Functional Safety theorems that bound side effects under those assumptions. Empirical evaluations on long-form document rewriting, code refactoring, and multi-page policy briefs substantially reduce side effects relative to baselines. These results demonstrate that principles from functional programming—explicit structure, composability, and controlled side effects—provide a rigorous foundation for reliable LLM-driven editing.