collaborators

7 papers

cs.PL2026

Coexponential Exploration in the Clef Programming Language

Houston Haynes

Clef was created as a concurrent programming language whose compiler tracks state ownership, waiting computations and request dependencies. We develop a coexponential account of st…

cs.PL2026

Negative and Fractional Types in the Fidelity Framework

Houston Haynes

Programs routinely create temporary data, retain state and revisit earlier results. Negative and fractional types benefit those activities in a type-resolved account of computation…

cs.PL2026

Fixed-Point Scaffolding in the Clef Programming Language

Houston Haynes

Native compilation changes how a program represents values and performs operations from processor to processor. In our view, proofs that justify source-level decisions must remain…

cs.PL2026

Decidable By Construction: Design-Time Verification for Truly Fearless Systems

Houston Haynes

Concurrency, parallelism and distributed execution become truly fearless when the compiler tracks wait-for edges, proves multi-threaded work is sound and preserves distributed boun…

cs.AI2026

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI

Houston Haynes

Transformer-based large language models have become a prominent focus of machine learning. We develop adaptive domain models to supply domain-specific predictions and checks within…

cs.PL2026

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation

Houston Haynes

Source code organizes a program as expressions and declarations, which a compiler can represent as an abstract syntax tree (AST). Some compilers introduce a further abstraction of…

cs.PL2026

Dimensional Type Systems and Deterministic Memory Management

Houston Haynes

We present a dimensional type system whose annotations remain available through the stages that require them, allowing numeric representation and deterministic memory management to…