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For a fixed effective machine coding, the predicate that program $e$ on input $x$ halts within $t$ steps is primitive recursive. Code finite configurations, iterate a total single-step function by primitive recursion, and test for the halt state. This supplies a bounded simulation even though the unrestricted halting problem is undecidable.

Search over the finite interval $0\le y\le b$ for the least witness to a primitive recursive predicate, with an explicitly chosen default if there is none. The result is a primitive recursive function, by scanning this finite interval using primitive recursion. This differs from unbounded minimization, which may fail to terminate.

With the Church Booleans $\mathsf{T}=\lambda ab.a$ and $\mathsf{F}=\lambda ab.b$, encode a pair byThen $\mathsf{Fst}(\mathsf{Pair}AB){\to }_{\beta }^{\ast }A$ and the second projection similarly returns $B$. Pairing an iteration counter with a computed value implements primitive recursion using only Church numeral iteration.

In a primitive recursion, an existential representation of the step function may need a different witness tuple at every time. Code each coordinate of the finite witness array by a separate beta-function code pair. All row witnesses then have bounded remainder quantifiers under the bounded time quantifier, while the finitely many code pairs remain in the outer unrestricted existential block.

A function in intension is a finite description of a computation, such as a program or a formal construction expression. A function in extension is the resulting input-output map, including its domain if it is partial. Different descriptions may have the same extension: the programs that return $x$ directly and that compute $x+0$ describe the same function. Finite descriptions have Gödel numbers; equality of the resulting partial computable functions is a separate semantic question.

The primitive recursive functions are the smallest class of numerical functions containing the zero functions, the successor function and all projection functions, and closed under function composition in recursion theory and primitive recursion. More explicitly, from $g:{\mathbb{N}}^k\to \mathbb{N}$ and $h:{\mathbb{N}}^{k+2}\to \mathbb{N}$ the latter operation formsFor function composition in recursion theory, an $m$-ary $g$ and $k$-ary $h_1,\dots ,h_m$ give $g(h_1(\mathbf{x}),\dots ,h_m(\mathbf{x}))$. Zero functions of all allowed arities can be included, with nullary zero included if arity $0$ is part of the coding convention. Every resulting function is total: the initial functions are total, function composition in recursion theory preserves totality, and mathematical induction on $n$ verifies totality of primitive recursion. Applying structural induction for primitive recursive functions then covers all construction expressions.

Use a fixed effective Gödel numbering of finite tagged construction trees with decidable decoding. A node is tagged as zero, successor, projection, composition, or recursion. The primitive recursive syntax and arity checking algorithm first checks that the input decodes as a finite tree, then works upwards from its leaves. A projection tag $(k,j)$ is legal exactly when $1\le j\le k$, with output arity $k$. A composition node declares its output arity $k$ and is legal when its outer child has arity $m$, there are exactly $m$ inner children, and each has arity $k$; its arity is $k$. The declared arity also handles the case $m=0$. A recursion node is legal when its base child has arity $k$ and its step child has arity $k+2$; its arity is $k+1$. Zero and successor tags have their declared arities. Ill-formed nodes are rejected. The process terminates because there are only finitely many nodes. Thus, for each fixed $i$,This is a syntactic assertion about functions in intension. It does not assert that arbitrary machine indices computing primitive recursive functions form a decidable set. That extensional property is nontrivial, hence undecidable by Rice theorem. For an explicit reduction, given a program $e$ construct a program that, on every input, waits for ${\phi }_e(e)$ to halt and then returns $0$. Its extension is a primitive recursive function if $e\in K$, and otherwise is nowhere defined and so is not a primitive recursive function. A decision procedure for this latter semantic set would decide the diagonal halting set.

Enumerate the decidable syntax set $D_1$ in increasing code order as $p_0,p_1,\dots$. There are infinitely many such descriptions; iterating successor after a unary zero expression already supplies infinitely many. Let $F_p$ be the extension of a valid construction and defineTo compute $U$, find $p_n$ by the syntax test and interpret its finite construction tree. Evaluate function composition in recursion theory by evaluating the children, and evaluate primitive recursion by the prescribed finite loop of length equal to its final input. Termination follows from the totality argument above, so $U$ and $d$ are total computable functions.

If $d$ were a unary primitive recursive function, some construction $p_j$ would have extension $d$. Then the diagonal argument giveswhich is impossible. The displayed $d$ is total and computable but not primitive recursive. Repetitions of extensions in the enumeration cause no problem: every possible extension is represented, which is all the diagonal argument needs. The same argument shows that the two-variable interpreter $U$ cannot itself be primitive recursive.

We prove closure under the defining schemes for primitive recursive functions, keeping all unbounded existential variables outside a bounded arithmetic formula. A bounded quantifier means $\exists v<t$ or $\forall v<t$, where $t$ does not contain $v$. All formulas are interpreted in the standard natural numbers.

First we need a finite sequence code using only the permitted language of ordered rings. Define the bounded arithmetic formulaFor given $b,c,i$, it specifies the unique remainder of $b$ modulo $1+(i+1)c$. In particular the quotient and remainder variables are bounded by arithmetic terms; division is not a new language symbol.

Every finite list $a_0,\dots ,a_n$ can be coded by some pair $b,c$. Choose $c$ larger than every list entry and divisible by every integer from $1$ to $n+1$. The moduli $m_i=1+(i+1)c$ are pairwise coprime. Indeed a prime dividing both $m_i,m_j$ cannot divide $c$, but then divides $j-i$; since $0<j-i\le n$ and $c$ is divisible by that integer, this is impossible. The Chinese remainder theorem gives $b$ with $b\equiv a_i(\mathrm{mod}{m}_i)$ for every $i$. Since $a_i<c<m_i$, each $B(b,c,i,a_i)$ holds. This is Gödel beta-function sequence coding. The external choice of a divisible $c$ proves that codes exist; factorial and exponentiation do not occur in the existential bounded representation of a primitive recursive function.

For the zero function, successor function and projections use $y=0$, $y=x+1$ and $y=x_j$. These formulas need no auxiliary variables. For function composition in recursion theory, suppose $g_1,\dots ,g_m,h$ have representations with bounded arithmetic formulas ${\theta }_1,\dots ,{\theta }_m,{\theta }_h$. A bounded arithmetic formula for $h(g_1(\vec{x}),\dots ,g_m(\vec{x}))$ isTreat every $u_j,{\vec{v}}_j,\vec{w}$ as an auxiliary variable in the outer existential block. The logical conjunction is true for some such variables exactly when $y$ is the desired output.

Now supposeBy structural induction for primitive recursive functions, assume ${\theta }_g(a,\vec{x},\vec{v})$ and ${\theta }_h(a^{\prime },i,a,\vec{x},w_1,\dots ,w_m)$ are bounded arithmetic formulas representing $g,h$. We code the values $f(0,\vec{x}),\dots ,f(n,\vec{x})$ with $b,c$. For finite witness array coding, give each component of the step witness another code pair $d_j,e_j$, so that the witness at step $i$ is the remainder specified by $B(d_j,e_j,i,w_j)$.

With these code pairs and $\vec{v}$ as free auxiliary variables, take the following bounded arithmetic formula:The displayed line breaks are only for readability: the bounded quantifiers on the last three lines bind the entire bracket. If $m=0$, their empty block and logical conjunction are omitted. Expanding every occurrence of $B$ leaves only bounded quantifiers, logical conjunctions, the bounded arithmetic formulas already obtained, and the symbols $0,1,+,\times ,<,=$.

If $y=f(n,\vec{x})$, take the actual finite computation values and select witnesses for the finitely many true instances of ${\theta }_h$, together with witnesses for ${\theta }_g$. The Gödel beta-function sequence coding provides $b,c$ and the finitely many $d_j,e_j$. These make $\varphi$ true. Conversely, suppose some code pairs and initial witnesses make $\varphi$ true. The unique remainders of $b$ give values $a_0,\dots ,a_n$. The initial clause makes $a_0=g(\vec{x})$. Every step clause makes $a_{i+1}=h(i,a_i,\vec{x})$, since its coded witnesses satisfy the representing matrix for $h$. Induction on $i$ gives $a_i=f(i,\vec{x})$, and the final remainder clause gives $y=a_n$. This argument includes $n=0$, when the step condition is empty.

Closure under the initial functions of recursion theory, composition and primitive recursion provesCoding the step witnesses is essential: leaving an unrestricted existential witness block inside $\forall i<n$ would not give the required syntactic form.

We use untyped lambda calculus and normal-order beta reduction. The Church numeral for $n$ is $\overline{n}=\lambda s.\lambda z.s^{n}z$. A lambda term represents a partial function if on numeral inputs it has the correct numeral normal form exactly when the function is defined. We use a lambda simulation of a Turing machine; this also ensures that undefined computations do not accidentally produce an output through an ignored argument.

First all total primitive recursive functions are lambda-definable. The initial functions of recursion theory are represented byComposition is obtained by substitution of representing terms. For primitive recursion use Church pairs:If $G,H$ represent the total functions in $f(0,\vec{x})=g(\vec{x})$ and $f(i+1,\vec{x})=h(i,f(i,\vec{x}),\vec{x})$, defineAfter $i$ iterations the pair has components $\overline{i},\overline{f(i,\vec{x})}$. Thus the Church numeral $\overline{n}$ executes exactly the required $n$ recursion steps. Since these functions are total on numeral inputs, substitution for composition causes no undefined-argument issue.

Now fix a deterministic Turing machine computing the given partial computable function. Encode a configuration by its finite control state and two natural numbers for the tape portions on the two sides of the head, allowing blank bits beyond the finite nonblank tape. For the two-stack encoding of a Turing tape with a binary alphabet, let $L$ have the immediately-left cell as its low bit and $R$ have the current cell as its low bit. Reading and removing a bit use remainder and quotient by two. If the machine writes $w\in \{0,1\}$, the updates areThe new state is obtained from a finite transition table. These operations, the initial configuration, the halting test, and output decoding are total primitive recursive functions on configuration codes. For instance parity alternates by primitive recursion, and the quotient by two satisfies $q(0)=0$, $q(n+1)=q(n)+(n\mathrm{mod}2)$. A fixed finite alphabet can be handled by the same stack construction in a larger base. Choose a standard delimited input and output convention, for example unary words in a finite tape alphabet with a distinct blank symbol. Initialization is primitive recursive. On a halting configuration the output is a finite word; decoding can be implemented by a bounded scan of the encoded tape, with a default output for malformed words. This is total primitive recursive and introduces no additional unbounded search. Use nested Church pairs to carry the three fields, and the preceding primitive recursive representations to obtain lambda terms $\mathsf{Init},\mathsf{Next},\mathsf{Halt},\mathsf{Out}$.

Represent Church Booleans by $\mathsf{True}=\lambda ab.a$ and $\mathsf{False}=\lambda ab.b$. A Church numeral zero test is $\mathsf{IsZero}=\lambda n.n(\lambda z.\mathsf{False})\mathsf{True}$. Use a numerical test equal to zero on halting configurations and one otherwise; applying this zero test gives the required Boolean halting test. With the fixed-point combinatorputNormal-order reduction evaluates the halting test on the current configuration. If it is true, it selects the output branch without evaluating the recursive branch. Otherwise it advances the configuration and repeats. Induction on the number of machine steps shows that a computation halting with output $y$ makes $F\overline{x_1}\cdots \overline{x_k}$ reduce to $\overline{y}$.

If the machine never halts, the normal-order beta reduction repeatedly takes the recursive branch. Each individual configuration transition and test terminates, but there is always another required transition; hence the reduction never reaches a normal form. The normal-order normalization theorem says that a lambda term with a beta-normal form is normalized by normal-order beta reduction. Therefore in the nonhalting case there is no numeral normal form at all. We have provedConfluence of beta reduction ensures uniqueness of the resulting numeral. This handles genuinely partial computations. Simply composing terms for partial subcomputations would need extra care, because lambda reduction can discard an unevaluated argument.

For (1)(a), a primitive recursive function is obtained by a finite construction from the zero function, successor function and projection functions, using function composition in recursion theory and primitive recursion. The recursion rule, with parameters $\mathbf{x}$, isHere $g,h$ have already been constructed. All these functions are total on nonnegative integers: the initial functions are total, composition preserves totality, and ordinary mathematical induction proves totality of each recursion.

For (1)(b), use a shifted hyperoperation sequence, beginning with addition. Defineand, for each fixed $r\ge 0$, defineThe first three members are therefore addition, multiplication and exponentiation:The exponentiation convention includes $a^0=1$, hence $0^0=1$. The next member iterates exponentiation, with $H_3(a,0)=1$; there is no need for an exceptional domain restriction at $a=0$.

For (1)(c), $H_0$ is a primitive recursive function by its displayed recursion. If $H_r$ is a primitive recursive function, thenare primitive recursive functions, using constants, projection functions and function composition in recursion theory. Primitive recursion applied to $g_r,h_r$ gives $H_{r+1}$. Mathematical induction on the fixed rank $r$ proves every member of the sequence is primitive recursive. This does not assert that the joint three-variable evaluator $(r,a,b)\mapsto H_r(a,b)$ is a primitive recursive function.

For (2), as written, the answer is no: the empty set $X=\varnothing$ is semidecidable, whereas a total computable function from $\mathbb{N}$ to $\mathbb{N}$ always has a nonempty range. This is the only obstruction. To prove the stronger useful statement, suppose $X$ is a nonempty computably enumerable set and choose $x_0\in X$. Fix a Turing machine which halts exactly on the inputs in $X$. Its bounded halting predicateis primitive recursive: encode configurations arithmetically, iterate its total single-step operation $t$ times by primitive recursion, and check the halt state. A halted configuration is kept fixed. This is a bounded simulation, not unbounded waiting.

Fix a primitive recursive pairing function $⟨x,t⟩$ with primitive recursive inverse coordinate functions. For example, the Cantor pairing function has inverses obtained by bounded minimization. DefineThe two coordinate functions, the bounded predicate, and the finite case distinction are primitive recursive functions, so $f$ is a primitive recursive function. Its values always lie in $X$. Conversely, if $x\in X$, its computation halts within some finite $t$, and $f(⟨x,t⟩)=x$. ThusThe range need not be a computable set; deciding whether a value occurs anywhere in this total enumeration is an unbounded search.