The decoder is a left inverse of the encoder: stdDecode ∘ stdEncode = some.
s-m-n specification at the language level: w is in L(stdSmn e x) iff
⟨w, ⟨x⟩⟩ is in L(e).
A function f : ℕ → ℕ on TM indices is computable (behavior version):
there is a single index e such that stdSmn e x and f x define
extensionally equal behaviors for every x.
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A function f : ℕ → ℕ on TM indices is computable (language version):
there is an index e such that stdSmn e x and f x recognize the same
language for every x.
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Representability: every behavior-computable function h has an index e
witnessing its computability. (Restatement of the definition.)
The diagonal s-m-n function x ↦ stdSmn x x is computable.
Computable functions on indices are closed under composition (behavior version).
For every index e, partial application x ↦ stdSmn e x is computable.
Representability for the language version: any IsComputableLang function
is witnessed by an index.
The diagonal s-m-n function is computable at the language level.
Composition closure for language-computability.
For every e, partial application x ↦ stdSmn e x is language-computable.
For any bound n, there exists a TM M whose language is different from the
language of every TM whose encoding is shorter than n. (Used to construct
"large" TMs in the MIN_TM proof.)
Enumeration-search principle: if the set of encodings of indices satisfying
P is Turing-recognizable and t selects, for every M, a strictly longer
encoded index with P (t M), then t is language-computable.
The standard TMCoding instance for RecursionTheorem, packaging the
behavior-level encoding, pairing, s-m-n, and computability operations into the
abstract TMCoding Bool structure used by the recursion theorem development.
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The standard TMCoding instance for TuringMachine, packaging the
language-level data (languageOf, language-computability, enumSearch, etc.)
into a single coding used by the general TM theory.