8 papers
Governed Metaprogramming for Intelligent Systems: Reclassifying Eval as a Governed Effect
Alan L. McCann
AI systems increasingly synthesize executable structure at runtime: LLMs generate programs, agents construct workflows,self-improving systems modify their own behavior. In classica…
Cryptographic Registry Provenance: Structural Defense Against Dependency Confusion in AI Package Ecosystems
Alan L. McCann
Dependency confusion attacks exploit a structural gap in software distribution: once a package is installed, there is no cryptographic proof of which registry distributed it. Every…
Certified Purity for Cognitive Workflow Executors: From Static Analysis to Cryptographic Attestation
Alan L. McCann
We present a certified purity architecture that converts governance enforcement in cognitive workflow systems from a runtime convention into a structural capability boundary. A pri…
Algebraic Semantics of Governed Execution: Monoidal Categories, Effect Algebras, and Coterminous Boundaries
Alan L. McCann
We present an algebraic semantics for governed execution in which governance is axiomatized, compositional, and coterminous with expressibility. The framework, mechanized in 32 Roc…
Effect-Transparent Governance for AI Workflow Architectures: Semantic Preservation, Expressive Minimality, and Decidability Boundaries
Alan L. McCann
We present a machine-checked formalization of structurally governed AI workflow architectures and prove that effect-level governance can be imposed without reducing internal comput…
The Two Boundaries: Why Behavioral AI Governance Fails Structurally
Alan L. McCann
Every system that performs effects has two boundaries: what it can do (expressiveness) and what governance covers (governance). In nearly all deployed AI systems, these boundaries…