Technical Foundations
Digital Circuitality on an information-theoretic footing.
The model behind bounded computation, closure, and compositional control.
Entropy
Bounded states reduce informational uncertainty.
Closure
Φc marks the closure condition the compiler checks.
Composition
EVA makes sequence, parallel, and conditional flow explicit.
Formal Definition
Entropy is uncertainty. Bounded computation reduces it by constraining modeled states.
Digital Circuitality reduces uncertainty by structure, not sampling.
Full coherence means zero informational uncertainty
“Φc marks the closure condition checked before emission.”
Conventional Model
Testing reduces uncertainty
Conventional workflows sample behavior. Unchecked paths stay open.
Digital Circuitality
Uncertainty removal by structure
Bounded domains plus closed composition make modeled state deterministic.
EVA Algebra: Composition Operators
SEQ, PAR, and COND keep flow explicit before closure checks.
SEQ Sequential
One stage feeds the next stage.
PAR Parallel
Branches evaluate on the same input.
COND Conditional
Branch structure stays explicit before selection.
Academic Foundations
References for uncertainty, discipline, and information boundaries.
Shannon, C.E. (1948)
A Mathematical Theory of Communication.
Informational entropy foundations.
Dijkstra, E.W. (1976)
A Discipline of Programming.
Software verification discipline.
Kish, L.B. (2018)
Information vs Thermal Entropy.
Rigorous distinction of quantities.
The Engineering Philosophy
Digital Circuitality.
The theory behind BRIK64: software logic treated as bounded, composable circuits.