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\begin{theorem}
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\label{thm:completeness}
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For every $\mubci{i-1}$ program $f(\vec u ; \vec x)$ (which is in $\fphi i$), there is a $\Sigma^{\safe}_i$ formula $A_f(\vec u, \vec x)$ such that $\arith^i$ proves $\forall^{\normal} \vec u, \forall^{\safe} \vec x, \exists^{\safe} ! y. A_f(\vec u , \vec x , y )$ and $\Nat \models \forall \vec u , \vec x. A(\vec u , \vec x , f(\vec u ; \vec x))$.
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For every $\mubci{i-1}$ program $f(\vec u ; \vec x)$ (which is in $\fphi i$), there is a $\Sigma^{\safe}_i$ formula $A_f(\vec u, \vec x)$ such that $\arith^i$ proves $\forall^{\normal} \vec u, \forall^{\safe} \vec x, \exists^{\safe} ! y. A_f(\vec u , \vec x , y )$ and $\Nat \models \forall \vec u , \vec x. A_f(\vec u , \vec x , f(\vec u ; \vec x))$.
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\end{theorem}
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The rest of this section is devoted to a proof of this theorem.
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We proceed by structural induction on a $\mubc^{i-1} $ program, dealing with each case in the proceeding paragraphs.
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The property is easily verified for the class of initial functions of $\mubci{i-1}$: constant, projections, (binary) successors, predecessor, conditional. Now let us examine the three constructions: predicative minimisation, predicative (safe) recursion and composition.
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The property is easily verified for the class of initial functions of $\mubci{i-1}$: constant, projections, (binary) successors, predecessor, conditional. \patrick{Maybe we can refer here to Sect. \ref{sect:graphsbasicfunctions}.} Now let us examine the three constructions: predicative minimisation, predicative (safe) recursion and composition.
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\paragraph*{Predicative minimisation}
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Suppose $f(\vec u ; \vec x)$ is defined as $\mu x^{+1} . g(\vec u ; \vec x , x) =_2 0$.
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By definition $g$ is in $\mubci{i-2}$, and so by the inductive hypothesis there is a $\Sigma^{\safe}_{i-1}$ formula $A_g (\vec u , \vec x , x , y)$ computing the graph of $g$ such that,
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\todo{elaborate}
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\paragraph*{Other cases}
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\todo{}
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The proof of Thm \ref{thm:completeness} is thus completed.
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