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\section{Proof of completeness}\label{appendix:completeness}
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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, as already shown in 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 by predicative minimisation from $g$ (we then denote $f$ as 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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\[
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\arith^i \proves \forall \vec u^\normal . \forall \vec x^\safe , x^\safe . \exists ! y^\safe . A_g(\vec u , \vec x , x , y)
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\]
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Let us define $A_f(\vec u ; \vec x , z)$ as:
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\[
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\begin{array}{rl}
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&\left(
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z=0 \  \cand \ \forall x^\safe , y^\safe . (A_g (\vec u , \vec x , x, y) \cimp y=_2 1)
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\right) \\
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\cor & \left(
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\begin{array}{ll}
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z\neq 0 
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& \cand\   \forall y^\safe . (A_g (\vec u , \vec x , p z , y) \cimp y=_2 0 ) \\
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& \cand\ \forall x^\safe < p z . \forall y^\safe . (A_g (\vec u , \vec x , x , y) \cimp y=_2 1) 
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\end{array}
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\right)
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\end{array}
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\]
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Notice that $A_f$ is $\Pi^{\safe}_{i-1}$, since $A_g$ is $\Sigma^{\safe}_{i-1}$ and occurs only in negative context above, with additional safe universal quantifiers occurring in positive context.
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In particular this means $A_f$ is $\Sigma^{\safe}_i$.
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Now, to prove totality of $A_f$, we rely on $\Sigma^\safe_{i-1}$-minimisation, which is a consequence of $\cpind{\Sigma^\safe_i}$:
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\begin{lemma}
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	[Minimisation]
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	$\arith^i \proves \cmin{\Sigma^\safe_{i-1}}$.	
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	\end{lemma}
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	% see Thm 20 p. 58 in Buss' book.
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	%\begin{proof}
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	%\end{proof}
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	\begin{proof}
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	This Lemma is proved by using the same method as for the proof of the analogous result in the bounded arithmetic $S_2^{i+1}$ (see \cite{Buss86book}, Thm 20, p. 58).
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	Let $A(x)$ be a  $\Sigma^\safe_{i-1}$ formula, with $x$ in $\safe$. We define the formula $B(a,b,c)$ as:
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	$$ \forall x^{\safe}. (x < |a| \moins b \cimp \zerobit(x,c)) \cand \forall y^{\safe}<c. \neg A(y) \cand \exists y^{\safe} < 2^{|a|\moins b}.A(c+y)$$
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	where $a$ is in $\normal$, $b$ in $\normal$ and $c$ in $\safe$.  $B(a,b,c)$ is in $\Sigma^\safe_{i}$.
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	The intuitive idea of the proof is to observe that, if $A(a)$ is true for $a\neq 0$, then  $\exists x^{\safe}\leq a. B(a,b,x)$ holds for $b=0$, and to try to prove it for $b=|a|$, by using a length induction on $b$.
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	First, one can prove:
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	$$ (A(a) \cand a \neq 0) \cimp B(a,0,0).$$ 
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	And thus:
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	$$ (A(a) \cand a \neq 0) \cimp \exists x^{\safe}\leq a .B(a,0,x).$$ 
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	We then can check that the two following statements are provable:
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	$$
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	\begin{array}{rcl}
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	(b<|a| \cand B(a,b,c)\cand \exists y^{\safe}<2^{|a| \moins (b+1)}.A(c+y)) &\cimp& B(a,\succ{} b,c)\\
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	(b<|a| \cand B(a,b,c)\cand \forall y^{\safe}<2^{|a| \moins(b+1)}.  A(c+y)) &\cimp & B(a,\succ{} b, c+2^{|a| \moins (b+1)})
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        \end{array}
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$$
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Moreover we have: $A(a) \cand B(a,b,c) \cimp c\leq a$.
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From these three statements we deduce:
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$$(A(a) \cand a \neq 0 \cand b<|a| \cand \exists x^{\safe} \leq a. B(a,b,x)) \cimp \exists x^{\safe } \leq a.B(a,\succ{} b,x).$$
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The formula $\exists x\leq a. B(a,b,c)$ is in $\Sigma^{\safe}_{i}$, so by $\Sigma^{\safe}_{i}$-LIND on the formula $\exists x\leq a. B(a,b,c)$, with the variable $b$ which is in $\normal$,  we obtain:
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$$(A(a) \cand a \neq 0 ) \cimp \exists x^{\safe } \leq a.B(a,|a|,x).$$
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\patrick{Anupam, is it a valid instance of LIND? I think it is.}
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But $B(a,|a|,x)$ implies $(\forall y^{\safe}<x. \neg A(y))\cand A(x)$, so we have proven:
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$$(A(a) \cand a \neq 0 ) \cimp (\exists x^{\safe } \leq a. (\forall y^{\safe}<x. \neg A(y))\cand A(x))$$
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which is the $\Sigma_{i-1}^{\safe}$ axiom for $A$.
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	\end{proof}
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%	\patrick{Examining it superficially, I think indeed the proof of Buss can be adapted to our setting. But we should probably look again at that with more scrutiny.}
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	Now, working in $\arith^i$, let $\vec u \in \normal , \vec x \in \safe$ and let us prove:
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	\[
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	\exists !z^\safe  . A_f(\vec u ; \vec x , z)
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	\]
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	Suppose that $\exists x^\safe , y^\safe .  (A_g (\vec u ,\vec x , x , y) \cand y=_2 0)$.
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	We can apply minimisation due to the lemma above to find the least $x\in \safe$ such that $\exists y^\safe .  (A_g (\vec u ,\vec x , x , y) \cand y=_2 0)$, and we set $z = \succ 1 x$. So $x= p z$. 
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	%\todo{verify $z\neq 0$ disjunct.} 
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	Then $z \neq 0$ holds. Moreover we had  $\exists ! y^\safe . A_g(\vec u , \vec x , x , y)$. So we deduce that
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	$\forall y^\safe . (A_g (\vec u , \vec x , p z , y) \cimp y=_2 0 ) $. Finally, as $p z$ is the least element such that
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	$\exists y^\safe .  (A_g (\vec u ,\vec x , p z , y) \cand y=_2 0)$, we deduce 
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	$\ \forall x^\safe < p z . \forall y^\safe . (A_g (\vec u , \vec x , x , y) \cimp y=_2 1) $. We conclude that the second member of the disjunction
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	$A_f(\vec u ; \vec x , z)$ is proven.  
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	Otherwise, we have that $\forall x^\safe , y^\safe . (A_g (\vec u , \vec x , x, y) \cimp y=_2 1)$, so we can set $z=0$ and the first member of the disjunction $A_f(\vec u ; \vec x , z)$ is proven.  
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	So we have proven $\exists z^\safe  . A_f(\vec u ; \vec x , z)$, and unicity can be easily verified.
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	\paragraph*{Predicative recursion on notation}
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	\anupam{Assume access to the following predicates (makes completeness easier, soundness will be okay):
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		\begin{itemize}
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			%	\item $\pair x y z $ . ``$z$ is the sequence that appends $y$ to the sequence $x$''
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			\item $\pair x y z$. ``$z$ is the sequence that prepends $x$ to the sequence $y$''
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			\item $\beta (i; x ,y)$. ``The $i$th element of the sequence $x$ is $y$.''
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			\end{itemize}
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			}
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			\patrick{I also assume access to the following predicates:
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				\begin{itemize}
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					%   \item $\zerobit (u,k)$ (resp. $\onebit(u,k)$). " The $k$th bit of $u$ is 0 (resp. 1)"
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					%   \item $\pref(k,x,y)$. "The prefix of $x$ (as a binary string) of length $k$ is $y$" 
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					\item $\addtosequence(w,y,w')$. "$w'$ represents the sequence obtained by adding $y$ at the end of the sequence represented by $w$". Here we are referring to sequences which can be decoded with predicate $\beta$.
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					\end{itemize}}
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					In the following we will use the predicates $\zerobit (u,k)$, $\onebit(u,k)$, $\pref(k,x,y)$ which have been defined in Sect. \ref{sect:graphsbasicfunctions}.
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					Suppose that $f$ is defined by predicative recursion on notation:
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					\[
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					\begin{array}{rcl}
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					f(0 , \vec u ; \vec x) & \dfn & g(\vec u ; \vec x) \\
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					f(\succ i u, \vec u ; \vec x) & \dfn & h_i( u , \vec u ; \vec x , f(u , \vec u ; \vec x))
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					\end{array}
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					\]
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					\anupam{using $\beta(i,x,y)$ predicate for sequences: ``$i$th element of $x$ is $y$''. Provably total in $\arith^1$.}
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					Suppose we have $\Sigma^\safe_i$ formulae $A_g (\vec u ; \vec x,y)$ and $A_{h_i} (u , \vec u ; \vec x , y , z)$ computing the graphs of $g$ and $h_i$ respectively, provably total in $\arith^i$.
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					We define $A_f (u ,\vec u ; \vec x , y)$ as,
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					\[
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					\exists w^\safe . \left(
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					\begin{array}{ll}
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					& 
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					%Seq(z) \cand 
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					\exists^{\safe} y_0 . ( A_g (\vec u , \vec x , y_0) \cand \beta(0, w , y_0) ) \cand \beta(|u|, w,y ) \\
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					%\cand & \forall k < |u| . \exists y_k , y_{k+1} . ( \beta (k, w, y_k) \cand \beta (k+1 ,w, y_{k+1})  \cand A_{h_i} (u , \vec u ; \vec x , y_k , y_{k+1}) )\\
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					\cand & \forall^{\normal}  k < |u| . \exists^{\safe} y_k , y_{k+1} . ( \beta (k, w, y_k) \cand \beta (k+1 ,w, y_{k+1})  \cand B (u , \vec u ; \vec x , y_k , y_{k+1}) )
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					\end{array}
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					\right)
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					\]
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					where 
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					\[
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					B (u , \vec u ; \vec x , y_k , y_{k+1}) = \left(
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					\begin{array}{ll}
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					& \zerobit(u,k+1) \cimp  \exists v .(\pref(k,u,v)  \cand A_{h_0}(v,\vec u ; \vec x, y_k, y_{k+1}) )\\
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					\cand &  \onebit(u,k+1) \cimp  \exists v .(\pref(k,u,v)  \cand A_{h_1}(v,\vec u ; \vec x, y_k, y_{k+1}) )
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					\end{array}
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					\right)
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					\]
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					%which is $\Sigma^\safe_i$ by inspection, and indeed defines the graph of $f$.
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					To show totality, let $\vec u \in \normal, \vec x \in \safe$ and proceed by induction on $u \in \normal$.
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					The base case, when $u=0$, is immediate from the totality of $A_g$, so for the inductive case we need to show:
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					\[
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					\exists y^\safe . A_f (u , \vec u ; \vec x , y) 
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					\quad \seqar \quad
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					\exists z^\safe . A_f (s_i u, \vec u ; \vec x , z)
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					\]
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					So let us assume $\exists y^\safe . A_f (u , \vec u ; \vec x , y) $. Then there exists $w$ such that $\safe(w)$ and 
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					$A_f (u , \vec u ; \vec x , w) $.
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					We know that there exists a $z$ such that $A_{h_i}(u,\vec u ; \vec x, y, z)$. Let then $w'$ be such that
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					$\addtosequence(w,z,w')$. Observe also that we have $\pref(|u|,s_i u,u)$
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					So we have, for $k=|u|$:
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					$$  \beta (k, w', y) \cand \beta (k+1 ,w', z)  \cand B (u , \vec u ; \vec x , y , z).$$
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					and we can conclude that
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					\[
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					\exists w'^\safe . \left(
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					\begin{array}{ll}
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					& 
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					%Seq(z) \cand 
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					\exists y_0 . ( A_g (\vec u , \vec x , y_0) \cand \beta(0, w' , y_0) ) \cand \beta(|u|+1, w',z ) \\
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					\cand & \forall k < |u|+1 . \exists y_k , y_{k+1} . ( \beta (k, w, y_k) \cand \beta (k+1 ,w, y_{k+1})  \cand B (u , \vec u ; \vec x , y_k , y_{k+1}) )
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					\end{array}
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					\right)
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					\]
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					So $\exists z^{\safe} . A_f (s_i u, \vec u ; \vec x , z)$ has been proven. So by induction we have proven $\forall^{\normal} u,  
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					\forall^{\normal} \vec u, \exists^{\safe} y. A_f (u ,\vec u ; \vec x , y)$. Moreover one can also check the unicity of $y$, and so we have proved the required formula. 
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					\anupam{here need to `add' element to the computation sequence. Need to do this earlier in the paper.}
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					\anupam{for inductive cases, need $u\neq 0$ for $\succ 0$ case.}
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					\paragraph*{Safe composition}
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					Now suppose that $f$ is defined by safe composition:
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					\[
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					f(\vec u ; \vec x) \quad \dfn \quad g( \vec h(\vec u;) ; \vec h' (\vec u ; \vec x) )
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					\]
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					By the inductive hypothesis, let us suppose that we have $\Sigma^\safe_i $ definitions $A_g , A_{h_i} , A_{h_j'} $ of the graphs of $g , h_i , h_j'$ respectively, which are provably total etc.
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					In particular, by Raising, we have that $\forall \vec u^\normal . \exists v^\normal . A_{h_i} (\vec u , v)$.
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					We define $A_f (\vec u , \vec x , z)$ defining the graph of $f$ as follows:
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					\[
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					\exists \vec v^\normal . \exists \vec y^\safe .  
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					\left(  
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					\bigwedge\limits_i A_{h_i} (\vec u , v_i)
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					\wedge
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					\bigwedge\limits_j A_{h_j'} (\vec u ; \vec x , y_j)
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					\wedge
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					A_g ( \vec v , \vec y , z ) 
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					\right)
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					\]
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					The provable totality of $A_f$ follows from simple first-order reasoning, mostly cuts and basic quantifier manipulations.
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					\todo{elaborate}
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					The proof of Thm \ref{thm:completeness} is thus completed.