Theory TOTAL_CONS

section ‹TOTAL is a proper subset of CONS\label{s:total_cons}›

theory TOTAL_CONS
  imports Lemma_R  (* for r_auxhyp *)
    CP_FIN_NUM  (* for r_consistent *)
    CONS_LIM  (* for rmge2, goedel_at *)
begin

text ‹We first show that TOTAL is a subset of CONS. Then we present a
separating class.›


subsection ‹TOTAL is a subset of CONS›

text ‹A TOTAL strategy hypothesizes only total functions, for which the
consistency with the input prefix is decidable. A CONS strategy can thus run
a TOTAL strategy and check if its hypothesis is consistent. If so, it
outputs this hypothesis, otherwise some arbitrary consistent one. Since the
TOTAL strategy converges to a correct hypothesis, which is consistent, the
CONS strategy will converge to the same hypothesis.›

text ‹Without loss of generality we can assume that learning takes place
with respect to our Gödel numbering $\varphi$. So we need to decide
consistency only for this numbering.›

abbreviation r_consist_phi where
  "r_consist_phi  r_consistent r_phi"

lemma r_consist_phi_recfn [simp]: "recfn 2 r_consist_phi"
  by simp

lemma r_consist_phi:
  assumes "k<e_length e. φ i k "
  shows "eval r_consist_phi [i, e] ↓=
    (if k<e_length e. φ i k ↓= e_nth e k then 0 else 1)"
proof -
  have "k<e_length e. eval r_phi [i, k] "
    using assms phi_def by simp
  moreover have "recfn 2 r_phi" by simp
  ultimately have "eval (r_consistent r_phi) [i, e] ↓=
     (if k<e_length e. eval r_phi [i, k] ↓= e_nth e k then 0 else 1)"
    using r_consistent_converg assms by simp
  then show ?thesis using phi_def by simp
qed

lemma r_consist_phi_init:
  assumes "f  " and "φ i  "
  shows "eval r_consist_phi [i, f  n] ↓= (if kn. φ i k = f k then 0 else 1)"
  using assms r_consist_phi R1_imp_total1 total1E by (simp add: r_consist_phi)

lemma TOTAL_subseteq_CONS: "TOTAL  CONS"
proof
  fix U assume "U  TOTAL"
  then have "U  TOTAL_wrt φ"
    using TOTAL_wrt_phi_eq_TOTAL by blast
  then obtain t' where t': "learn_total φ U t'"
    using TOTAL_wrt_def by auto
  then obtain t where t: "recfn 1 t" "x. eval t [x] = t' x"
    using learn_totalE(1) P1E by blast
  then have t_converg: "eval t [f  n] " if "f  U" for f n
    using t' learn_totalE(1) that by auto

  define s where "s  Cn 1 r_ifz [Cn 1 r_consist_phi [t, Id 1 0], t, r_auxhyp]"
  then have "recfn 1 s"
    using r_consist_phi_recfn r_auxhyp_prim t(1) by simp

  have consist: "eval r_consist_phi [the (eval t [f  n]), f  n] ↓=
     (if kn. φ (the (eval t [f  n])) k = f k then 0 else 1)"
    if "f  U" for f n
  proof -
    have "eval r_consist_phi [the (eval t [f  n]), f  n] =
        eval (Cn 1 r_consist_phi [t, Id 1 0]) [f  n]"
      using that t_converg t(1) by simp
    also have "... ↓= (if kn. φ (the (eval t [f  n])) k = f k then 0 else 1)"
    proof -
      from that have "f  "
        using learn_totalE(1) t' by blast
      moreover have "φ (the (eval t [f  n]))  "
        using t' t learn_totalE t_converg that by simp
      ultimately show ?thesis
        using r_consist_phi_init t_converg t(1) that by simp
    qed
    finally show ?thesis .
  qed

  have s_eq_t: "eval s [f  n] = eval t [f  n]"
    if "kn. φ (the (eval t [f  n])) k = f k" and "f  U" for f n
    using that consist s_def t r_auxhyp_prim prim_recfn_total
    by simp

  have s_eq_aux: "eval s [f  n] = eval r_auxhyp [f  n]"
    if "¬ (kn. φ (the (eval t [f  n])) k = f k)" and "f  U" for f n
  proof -
    from that have "eval r_consist_phi [the (eval t [f  n]), f  n] ↓= 1"
      using consist by simp
    moreover have "t' (f  n) " using t' learn_totalE(1) that(2) by blast
    ultimately show ?thesis
      using s_def t r_auxhyp_prim t' learn_totalE by simp
  qed

  have "learn_cons φ U (λe. eval s [e])"
  proof (rule learn_consI)
    have "eval s [f  n] " if "f  U" for f n
      using that t_converg[OF that, of n] s_eq_t[of n f] prim_recfn_total[of r_auxhyp 1]
        r_auxhyp_prim s_eq_aux[OF _ that, of n] totalE
      by fastforce
    then show "environment φ U (λe. eval s [e])"
      using t' recfn 1 s learn_totalE(1) by blast
    show "i. φ i = f  (n. eval s [f  n] ↓= i)" if "f  U" for f
    proof -
      from that t' t learn_totalE obtain i n0 where
        i_n0: "φ i = f  (nn0. eval t [f  n] ↓= i)"
        by metis
      then have "n. n  n0  kn. φ (the (eval t [f  n])) k = f k"
        by simp
      with s_eq_t have "n. n  n0  eval s [f  n] = eval t [f  n]"
        using that by simp
      with i_n0 have "n. n  n0  eval s [f  n] ↓= i"
        by auto
      with i_n0 show ?thesis by auto
    qed
    show "kn. φ (the (eval s [f  n])) k = f k" if "f  U" for f n
    proof (cases "kn. φ (the (eval t [f  n])) k = f k")
      case True
      with that s_eq_t show ?thesis by simp
    next
      case False
      then have "eval s [f  n] = eval r_auxhyp [f  n]"
        using that s_eq_aux by simp
      moreover have "f  "
        using learn_totalE(1)[OF t'] that by auto
      ultimately show ?thesis using r_auxhyp by simp
    qed
  qed
  then show "U  CONS" using CONS_def by auto
qed


subsection ‹The separating class›


subsubsection ‹Definition of the class›

text ‹The class that will be shown to be in @{term "CONS - TOTAL"} is
the union of the following two classes.›

definition V_constotal_1 :: "partial1 set" where
  "V_constotal_1  {f. j p. f = [j]  p  j  2  p  01  φ j = f}"

definition V_constotal_2 :: "partial1 set" where
  "V_constotal_2 
     {f. j a k.
            f = j # a @ [k]  0 
            j  2 
            (i<length a. a ! i  1) 
            k  2 
            φ j = j # a   
            φ k = f}"

definition V_constotal :: "partial1 set" where
  "V_constotal  V_constotal_1  V_constotal_2"

lemma V_constotal_2I:
  assumes "f = j # a @ [k]  0"
    and "j  2"
    and "i<length a. a ! i  1"
    and "k  2"
    and "φ j = j # a  "
    and "φ k = f"
  shows "f  V_constotal_2"
  using assms V_constotal_2_def by blast

lemma V_subseteq_R1: "V_constotal  "
proof
  fix f assume "f  V_constotal"
  then have "f  V_constotal_1  f  V_constotal_2"
    using V_constotal_def by auto
  then show "f  "
  proof
    assume "f  V_constotal_1"
    then obtain j p where "f = [j]  p" "p  01"
      using V_constotal_1_def by blast
    then show ?thesis using prepend_in_R1 RPred1_subseteq_R1 by auto
  next
    assume "f  V_constotal_2"
    then obtain j a k where "f = j # a @ [k]  0"
      using V_constotal_2_def by blast
    then show ?thesis using almost0_in_R1 by auto
  qed
qed


subsubsection ‹The class is in CONS›

text ‹The class can be learned by the strategy @{term rmge2}, which
outputs the rightmost value greater or equal two in the input $f^n$. If $f$
is from $V_1$ then the strategy is correct right from the start. If $f$ is
from $V_2$ the strategy outputs the consistent hypothesis $j$ until it
encounters the correct hypothesis $k$, to which it converges.›

lemma V_in_CONS: "learn_cons φ V_constotal rmge2"
proof (rule learn_consI)
  show "environment φ V_constotal rmge2"
    using V_subseteq_R1 rmge2_in_R1 R1_imp_total1 phi_in_P2 by simp
  have "(i. φ i = f  (n. rmge2 (f  n) ↓= i)) 
      (n. kn. φ (the (rmge2 (f  n))) k = f k)"
    if "f  V_constotal" for f
  proof (cases "f  V_constotal_1")
    case True
    then obtain j p where
      f: "f = [j]  p" and
      j: "j  2" and
      p: "p  01" and
      phi_j: "φ j = f"
      using V_constotal_1_def by blast
    then have "f 0 ↓= j" by (simp add: prepend_at_less)
    then have f_at_0: "the (f 0)  2" by (simp add: j)
    have f_at_gr0: "the (f x)  1" if "x > 0" for x
      using that f p by (simp add: RPred1_altdef Suc_leI prepend_at_ge)
    have "total1 f"
      using V_subseteq_R1 that R1_imp_total1 total1_def by auto
    have "rmge2 (f  n) ↓= j" for n
    proof -
      let ?P = "λi. i < Suc n  the (f i)  2"
      have "Greatest ?P = 0"
      proof (rule Greatest_equality)
        show "0 < Suc n  2  the (f 0)"
          using f_at_0 by simp
        show "y. y < Suc n  2  the (f y)  y  0"
          using f_at_gr0 by fastforce
      qed
      then have "rmge2 (f  n) = f 0"
        using f_at_0 rmge2_init_total[of f n, OF total1 f] by auto
      then show "rmge2 (f  n) ↓= j"
        by (simp add: f 0 ↓= j)
    qed
    then show ?thesis using phi_j by auto
  next
    case False
    then have "f  V_constotal_2"
      using V_constotal_def that by auto
    then obtain j a k where jak:
      "f = j # a @ [k]  0"
      "j  2"
      "i<length a. a ! i  1"
      "k  2"
      "φ j = j # a   "
      "φ k = f"
      using V_constotal_2_def by blast
    then have f_at_0: "f 0 ↓= j" by simp
    have f_eq_a: "f x ↓= a ! (x - 1)" if "0 < x  x < Suc (length a)" for x
    proof -
      have "x - 1 < length a"
        using that by auto
      then show ?thesis
        by (simp add: jak(1) less_SucI nth_append that)
    qed
    then have f_at_a: "the (f x)  1" if "0 < x  x < Suc (length a)" for x
      using jak(3) that by auto
    from jak have f_k: "f (Suc (length a)) ↓= k" by auto
    from jak have f_at_big: "f x ↓= 0" if "x > Suc (length a)" for x
      using that by simp
    let ?P = "λn i. i < Suc n  the (f i)  2"
    have rmge2: "rmge2 (f  n) = f (Greatest (?P n))" for n
    proof -
      have "¬ (i<Suc n. the (f i) < 2)" for n
        using jak(2) f_at_0 by auto
      moreover have "total1 f"
        using V_subseteq_R1 R1_imp_total1 that total1_def by auto
      ultimately show ?thesis using rmge2_init_total[of f n] by auto
    qed
    have "Greatest (?P n) = 0" if "n < Suc (length a)" for n
    proof (rule Greatest_equality)
      show "0 < Suc n  2  the (f 0)"
        using that by (simp add: jak(2) f_at_0)
      show "y. y < Suc n  2  the (f y)  y  0"
        using that f_at_a
        by (metis Suc_1 dual_order.strict_trans leI less_Suc_eq not_less_eq_eq)
    qed
    with rmge2 f_at_0 have rmge2_small:
      "rmge2 (f  n) ↓= j" if "n < Suc (length a)" for n
      using that by simp
    have "Greatest (?P n) = Suc (length a)" if "n  Suc (length a)" for n
    proof (rule Greatest_equality)
      show "Suc (length a) < Suc n  2  the (f (Suc (length a)))"
        using that f_k by (simp add: jak(4) less_Suc_eq_le)
      show "y. y < Suc n  2  the (f y)  y  Suc (length a)"
        using that f_at_big by (metis leI le_SucI not_less_eq_eq numeral_2_eq_2 option.sel)
    qed
    with rmge2 f_at_big f_k have rmge2_big:
      "rmge2 (f  n) ↓= k" if "n  Suc (length a)" for n
      using that by simp
    then have "i n0. φ i = f  (nn0. rmge2 (f  n) ↓= i)"
      using jak(6) by auto
    moreover have "kn. φ (the (rmge2 (f  n))) k = f k" for n
    proof (cases "n < Suc (length a)")
      case True
      then have "rmge2 (f  n) ↓= j"
        using rmge2_small by simp
      then have "φ (the (rmge2 (f  n))) = φ j" by simp
      with True show ?thesis
        using rmge2_small f_at_0 f_eq_a jak(5) prepend_at_less
        by (metis le_less_trans le_zero_eq length_Cons not_le_imp_less nth_Cons_0 nth_Cons_pos)
    next
      case False
      then show ?thesis using rmge2_big jak by simp
    qed
    ultimately show ?thesis by simp
  qed
  then show "f. f  V_constotal  i. φ i = f  (n. rmge2 (f  n) ↓= i)"
    and "f n. f  V_constotal  kn. φ (the (rmge2 (f  n))) k = f k"
    by simp_all
qed


subsubsection ‹The class is not in TOTAL›

text ‹Recall that $V$ is the union of $V_1 = \{jp \mid j\geq2 \land p \in
\mathcal{R}_{01} \land \varphi_j = jp\}$ and $V_2 = \{jak0^\infty \mid j\geq 2 \land a
\in \{0, 1\}^* \land k\geq 2 \land \varphi_j = ja\uparrow^\infty \land\ 
\varphi_k = jak0^\infty\}$.›

text ‹The proof is adapted from a proof of a stronger result by
Freivalds, Kinber, and Wiehagen~cite‹Theorem~27› in "fkw-iisde-95" concerning an
inference type not defined here.

The proof is by contradiction. If $V$ was in TOTAL, there would be
a strategy $S$ learning $V$ in our standard Gödel numbering $\varphi$.
By Lemma R for TOTAL we can assume $S$ to be total.

In order to construct a function $f\in V$ for which $S$ fails we employ a
computable process iteratively building function prefixes. For every $j$ the
process builds a function $\psi_j$. The initial prefix is the singleton
$[j]$. Given a prefix $b$, the next prefix is determined as follows:
\begin{enumerate}
\item Search for a $y \geq |b|$ with $\varphi_{S(b)}(y) \downarrow= v$ for
some $v$.
\item Set the new prefix $b0^{y - |b|}\bar{v}$, where $\bar v = 1 - v$.
\end{enumerate}

Step~1 can diverge, for example, if $\varphi_{S(b)}$ is the empty function.
In this case $\psi_j$ will only be defined for a finite prefix. If, however,
Step~2 is reached, the prefix $b$ is extended to a $b'$ such that
$\varphi_{S(b)}(y) \neq b'_y$, which implies $S(b)$ is a wrong hypothesis for
every function starting with $b'$, in particular for $\psi_j$. Since $\bar v
\in \{0, 1\}$, Step~2 only appends zeros and ones, which is important for
showing membership in $V$.

This process defines a numbering $\psi \in \mathcal{P}^2$, and by Kleene's
fixed-point theorem there is a $j \geq 2$ with $\varphi_j = \psi_j$. For this
$j$ there are two cases:
\begin{enumerate}
\item[Case 1.] Step~1 always succeeds. Then $\psi_j$ is total and
  $\psi_j \in V_1$. But $S$ outputs wrong hypotheses on infinitely many
  prefixes of $\psi_j$ (namely every prefix constructed by the process).

\item[Case 2.] Step~1 diverges at some iteration, say when the state is $b = ja$
  for some $a \in \{0, 1\}^*$.
  Then $\psi_j$ has the form $ja\uparrow^\infty$. The numbering $\chi$ with $\chi_k =
  jak0^\infty$ is in $\mathcal{P}^2$, and by Kleene's fixed-point theorem there is a
  $k\geq 2$ with $\varphi_k = \chi_k = jak0^\infty$. This $jak0^\infty$ is in
  $V_2$ and has the prefix $ja$. But Step~1 diverged on this prefix, which
  means there is no $y \geq |ja|$ with $\varphi_{S(ja)}(y)\downarrow$. In
  other words $S$ hypothesizes a non-total function.
\end{enumerate}

Thus, in both cases there is a function in $V$ where $S$ does not behave like
a TOTAL strategy. This is the desired contradiction.

The following locale formalizes this proof sketch.›

locale total_cons =
  fixes s :: partial1
  assumes s_in_R1: "s  "
begin

definition r_s :: recf where
  "r_s  SOME r_s. recfn 1 r_s   total r_s  s = (λx. eval r_s [x])"

lemma rs_recfn [simp]: "recfn 1 r_s"
  and rs_total [simp]: "x. eval r_s [x] "
  and eval_rs: "x. s x = eval r_s [x]"
  using r_s_def R1_SOME[OF s_in_R1, of r_s] by simp_all

text ‹Performing Step~1 means enumerating the domain of
$\varphi_{S(b)}$ until a $y \geq |b|$ is found. The next function enumerates
all domain values and checks the condition for them.›

definition "r_search_enum 
  Cn 2 r_le [Cn 2 r_length [Id 2 1], Cn 2 r_enumdom [Cn 2 r_s [Id 2 1], Id 2 0]]"

lemma r_search_enum_recfn [simp]: "recfn 2 r_search_enum"
  by (simp add: r_search_enum_def Let_def)

abbreviation search_enum :: partial2 where
  "search_enum x b  eval r_search_enum [x, b]"

abbreviation enumdom :: partial2 where
  "enumdom i y  eval r_enumdom [i, y]"

lemma enumdom_empty_domain:
  assumes "x. φ i x "
  shows "y. enumdom i y "
  using assms r_enumdom_empty_domain by (simp add: phi_def)

lemma enumdom_nonempty_domain:
  assumes "φ i x0 "
  shows "y. enumdom i y "
   and "x. φ i x   (y. enumdom i y ↓= x)"
  using assms r_enumdom_nonempty_domain phi_def by metis+

text ‹Enumerating the empty domain yields the empty function.›

lemma search_enum_empty:
  fixes b :: nat
  assumes "s b ↓= i" and "x. φ i x "
  shows "x. search_enum x b "
  using assms r_search_enum_def enumdom_empty_domain eval_rs by simp

text ‹Enumerating a non-empty domain yields a total function.›

lemma search_enum_nonempty:
  fixes b y0 :: nat
  assumes "s b ↓= i" and "φ i y0 " and "e = the (enumdom i x)"
  shows "search_enum x b ↓= (if e_length b  e then 0 else 1)"
proof -
  let ?e = "λx. the (enumdom i x)"
  let ?y = "Cn 2 r_enumdom [Cn 2 r_s [Id 2 1], Id 2 0]"
  have "recfn 2 ?y" using assms(1) by simp
  moreover have "x. eval ?y [x, b] = enumdom i x"
    using assms(1,2) eval_rs by auto
  moreover from this have "x. eval ?y [x, b] "
    using enumdom_nonempty_domain(1)[OF assms(2)] by simp
  ultimately have "eval (Cn 2 r_le [Cn 2 r_length [Id 2 1], ?y]) [x, b] ↓=
      (if e_length b  ?e x then 0 else 1)"
    by simp
  then show ?thesis using assms by (simp add: r_search_enum_def)
qed

text ‹If there is a $y$ as desired, the enumeration will eventually return
zero (representing ``true'').›

lemma search_enum_nonempty_eq0:
  fixes b y :: nat
  assumes "s b ↓= i" and "φ i y " and "y  e_length b"
  shows "x. search_enum x b ↓= 0"
proof -
  obtain x where x: "enumdom i x ↓= y"
    using enumdom_nonempty_domain(2)[OF assms(2)] assms(2) by auto
  from assms(2) have "φ i y " by simp
  with x have "search_enum x b ↓= 0"
    using search_enum_nonempty[where ?e=y] assms by auto
  then show ?thesis by auto
qed

text ‹If there is no $y$ as desired, the enumeration will never return
zero.›

lemma search_enum_nonempty_neq0:
  fixes b y0 :: nat
  assumes "s b ↓= i"
    and "φ i y0 "
    and "¬ (y. φ i y   y  e_length b)"
  shows "¬ (x. search_enum x b ↓= 0)"
proof
  assume "x. search_enum x b ↓= 0"
  then obtain x where x: "search_enum x b ↓= 0"
    by auto
  obtain y where y: "enumdom i x ↓= y"
    using enumdom_nonempty_domain[OF assms(2)] by blast
  then have "search_enum x b ↓= (if e_length b  y then 0 else 1)"
    using assms(1-2) search_enum_nonempty by simp
  with x have "e_length b  y"
    using option.inject by fastforce
  moreover have "φ i y "
    using assms(2) enumdom_nonempty_domain(2) y by blast
  ultimately show False using assms(3) by force
qed

text ‹The next function corresponds to Step~1. Given a prefix $b$ it
computes a $y \geq |b|$ with $\varphi_{S(b)}(y)\downarrow$ if such a $y$
exists; otherwise it diverges.›

definition "r_search  Cn 1 r_enumdom [r_s, Mn 1 r_search_enum]"

lemma r_search_recfn [simp]: "recfn 1 r_search"
  using r_search_def by simp

abbreviation search :: partial1 where
  "search b  eval r_search [b]"

text ‹If $\varphi_{S(b)}$ is the empty function, the search process
diverges because already the enumeration of the domain diverges.›

lemma search_empty:
  assumes "s b ↓= i" and "x. φ i x "
  shows "search b "
proof -
  have "x. search_enum x b "
    using search_enum_empty[OF assms] by simp
  then have "eval (Mn 1 r_search_enum) [b] " by simp
  then show "search b " unfolding r_search_def by simp
qed

text ‹If $\varphi_{S(b)}$ is non-empty, but there is no $y$ with the
desired properties, the search process diverges.›

lemma search_nonempty_neq0:
  fixes b y0 :: nat
  assumes "s b ↓= i"
    and "φ i y0 "
    and "¬ (y. φ i y   y  e_length b)"
  shows "search b "
proof -
  have "¬ (x. search_enum x b ↓= 0)"
    using assms search_enum_nonempty_neq0 by simp
  moreover have "recfn 1 (Mn 1 r_search_enum)"
    by (simp add: assms(1))
  ultimately have "eval (Mn 1 r_search_enum) [b] " by simp
  then show ?thesis using r_search_def by auto
qed

text ‹If there is a $y$ as desired, the search process will return
one such $y$.›

lemma search_nonempty_eq0:
  fixes b y :: nat
  assumes "s b ↓= i" and "φ i y " and "y  e_length b"
  shows "search b "
    and "φ i (the (search b)) "
    and "the (search b)  e_length b"
proof -
  have "x. search_enum x b ↓= 0"
    using assms search_enum_nonempty_eq0 by simp
  moreover have "x. search_enum x b "
    using assms search_enum_nonempty by simp
  moreover have "recfn 1 (Mn 1 r_search_enum)"
    by simp
  ultimately have
    1: "search_enum (the (eval (Mn 1 r_search_enum) [b])) b ↓= 0" and
    2: "eval (Mn 1 r_search_enum) [b] "
    using eval_Mn_diverg eval_Mn_convergE[of 1 "r_search_enum" "[b]"]
    by (metis (no_types, lifting) One_nat_def length_Cons list.size(3) option.collapse,
      metis (no_types, lifting) One_nat_def length_Cons list.size(3))
  let ?x = "the (eval (Mn 1 r_search_enum) [b])"
  have "search b = eval (Cn 1 r_enumdom [r_s, Mn 1 r_search_enum]) [b]"
    unfolding r_search_def by simp
  then have 3: "search b = enumdom i ?x"
    using assms 2 eval_rs by simp
  then have "the (search b) = the (enumdom i ?x)" (is "?y = _")
    by simp
  then have 4: "search_enum ?x b ↓= (if e_length b  ?y then 0 else 1)"
    using search_enum_nonempty assms by simp
  from 3 have "φ i ?y "
    using enumdom_nonempty_domain assms(2) by (metis option.collapse)
  then show "φ i ?y "
    using phi_def by simp
  then show "?y  e_length b"
    using assms 4 1 option.inject by fastforce
  show "search b "
    using 3 assms(2) enumdom_nonempty_domain(1) by auto
qed

text ‹The converse of the previous lemma states that whenever
the search process returns a value it will be one with the
desired properties.›

lemma search_converg:
  assumes "s b ↓= i" and "search b " (is "?y ")
  shows "φ i (the ?y) "
    and "the ?y  e_length b"
proof -
  have "y. φ i y "
    using assms search_empty by meson
  then have "y. y  e_length b  φ i y "
    using search_nonempty_neq0 assms by meson
  then obtain y where y: "y  e_length b  φ i y " by auto
  then have "φ i y "
    using phi_def by simp
  then show "φ i (the (search b)) "
    and "(the (search b))  e_length b"
    using y assms search_nonempty_eq0[OF assms(1) φ i y ] by simp_all
qed

text ‹Likewise, if the search diverges, there is no appropriate $y$.›

lemma search_diverg:
  assumes "s b ↓= i" and "search b "
  shows "¬ (y. φ i y   y  e_length b)"
proof
  assume "y. φ i y   y  e_length b"
  then obtain y where y: "φ i y " "y  e_length b"
    by auto
  from y(1) have "φ i y "
    by (simp add: phi_def)
  with y(2) search_nonempty_eq0 have "search b "
    using assms by blast
  with assms(2) show False by simp
qed

text ‹Step~2 extends the prefix by a block of the shape $0^n\bar v$.
The next function constructs such a block for given $n$ and $v$.›

definition "r_badblock 
  let f = Cn 1 r_singleton_encode [r_not];
      g = Cn 3 r_cons [r_constn 2 0, Id 3 1]
  in Pr 1 f g"

lemma r_badblock_prim [simp]: "recfn 2 r_badblock"
  unfolding r_badblock_def by simp

lemma r_badblock: "eval r_badblock [n, v] ↓= list_encode (replicate n 0 @ [1 - v])"
proof (induction n)
  case 0
  let ?f = "Cn 1 r_singleton_encode [r_not]"
  have "eval r_badblock [0, v] = eval ?f [v]"
    unfolding r_badblock_def by simp
  also have "... = eval r_singleton_encode [the (eval r_not [v])]"
    by simp
  also have "... ↓= list_encode [1 - v]"
    by simp
  finally show ?case by simp
next
  case (Suc n)
  let ?g = "Cn 3 r_cons [r_constn 2 0, Id 3 1]"
  have "recfn 3 ?g" by simp
  have "eval r_badblock [(Suc n), v] = eval ?g [n, the (eval r_badblock [n , v]), v]"
    using recfn 3 ?g Suc by (simp add: r_badblock_def)
  also have "... = eval ?g [n, list_encode (replicate n 0 @ [1 - v]), v]"
    using Suc by simp
  also have "... = eval r_cons [0, list_encode (replicate n 0 @ [1 - v])]"
    by simp
  also have "... ↓= e_cons 0 (list_encode (replicate n 0 @ [1 - v]))"
    by simp
  also have "... ↓= list_encode (0 # (replicate n 0 @ [1 - v]))"
    by simp
  also have "... ↓= list_encode (replicate (Suc n) 0 @ [1 - v])"
    by simp
  finally show ?case by simp
qed

lemma r_badblock_only_01: "e_nth (the (eval r_badblock [n, v])) i  1"
  using r_badblock by (simp add: nth_append)

lemma r_badblock_last: "e_nth (the (eval r_badblock [n, v])) n = 1 - v"
  using r_badblock by (simp add: nth_append)

text ‹The following function computes the next prefix from the current
one. In other words, it performs Steps~1 and~2.›

definition "r_next 
  Cn 1 r_append
   [Id 1 0,
    Cn 1 r_badblock
     [Cn 1 r_sub [r_search, r_length],
      Cn 1 r_phi [r_s, r_search]]]"

lemma r_next_recfn [simp]: "recfn 1 r_next"
  unfolding r_next_def by simp

text ‹The name @{text next} is unavailable, so we go for @{term nxt}.›

abbreviation nxt :: partial1 where
  "nxt b  eval r_next [b]"

lemma nxt_diverg:
  assumes "search b "
  shows "nxt b "
  unfolding r_next_def using assms by (simp add: Let_def)

lemma nxt_converg:
  assumes "search b ↓= y"
  shows "nxt b ↓=
     e_append b (list_encode (replicate (y - e_length b) 0 @ [1 - the (φ (the (s b)) y)]))"
  unfolding r_next_def using assms r_badblock search_converg phi_def eval_rs
  by fastforce

lemma nxt_search_diverg:
  assumes "nxt b "
  shows "search b "
proof (rule ccontr)
  assume "search b "
  then obtain y where "search b ↓= y" by auto
  then show False
    using nxt_converg assms by simp
qed

text ‹If Step~1 finds a $y$, the hypothesis $S(b)$ is incorrect for
the new prefix.›

lemma nxt_wrong_hyp:
  assumes "nxt b ↓= b'" and "s b ↓= i"
  shows "y<e_length b'. φ i y ↓≠ e_nth b' y"
proof -
  obtain y where y: "search b ↓= y"
    using assms nxt_diverg by fastforce
  then have y_len: "y  e_length b"
    using assms search_converg(2) by fastforce
  then have b': "b' =
      (e_append b (list_encode (replicate (y - e_length b) 0 @ [1 - the (φ i y)])))"
    using y assms nxt_converg by simp
  then have "e_nth b' y = 1 - the (φ i y)"
    using y_len e_nth_append_big r_badblock r_badblock_last by auto
  moreover have "φ i y "
    using search_converg y y_len assms(2) by fastforce
  ultimately have "φ i y ↓≠ e_nth b' y"
    by (metis gr_zeroI less_numeral_extra(4) less_one option.sel zero_less_diff)
  moreover have "e_length b' = Suc y"
    using y_len e_length_append b' by auto
  ultimately show ?thesis by auto
qed

text ‹If Step~1 diverges, the hypothesis $S(b)$ refers to a non-total
function.›

lemma nxt_nontotal_hyp:
  assumes "nxt b " and "s b ↓= i"
  shows "x. φ i x "
  using nxt_search_diverg[OF assms(1)] search_diverg[OF assms(2)] by auto

text ‹The process only ever extends the given prefix.›

lemma nxt_stable:
  assumes "nxt b ↓= b'"
  shows "x<e_length b. e_nth b x = e_nth b' x"
proof -
  obtain y where y: "search b ↓= y"
    using assms nxt_diverg by fastforce
  then have "y  e_length b"
    using search_converg(2) eval_rs rs_total by fastforce
  show ?thesis
  proof (rule allI, rule impI)
    fix x assume "x < e_length b"
    let ?i = "the (s b)"
    have b': "b' =
        (e_append b (list_encode (replicate (y - e_length b) 0 @ [1 - the (φ ?i y)])))"
      using assms nxt_converg[OF y] by auto
    then show "e_nth b x = e_nth b' x"
      using e_nth_append_small x < e_length b by auto
  qed
qed

text ‹The following properties of @{term r_next} will be
used to show that some of the constructed functions are in the class
$V$.›

lemma nxt_append_01:
  assumes "nxt b ↓= b'"
  shows "x. x  e_length b  x < e_length b'   e_nth b' x = 0  e_nth b' x = 1"
proof -
  obtain y where y: "search b ↓= y"
    using assms nxt_diverg by fastforce
  let ?i = "the (s b)"
  have b': "b' = (e_append b (list_encode (replicate (y - e_length b) 0 @ [1 - the (φ ?i y)])))"
    (is "b' = (e_append b ?z)")
    using assms y  nxt_converg prod_encode_eq by auto
  show ?thesis
  proof (rule allI, rule impI)
    fix x assume x: "e_length b  x  x < e_length b'"
    then have "e_nth b' x = e_nth ?z (x - e_length b)"
      using b' e_nth_append_big by blast
    then show "e_nth b' x = 0  e_nth b' x = 1"
      by (metis less_one nat_less_le option.sel r_badblock r_badblock_only_01)
  qed
qed

lemma nxt_monotone:
  assumes "nxt b ↓= b'"
  shows "e_length b < e_length b'"
proof -
  obtain y where y: "search b ↓= y"
    using assms nxt_diverg by fastforce
  let ?i = "the (s b)"
  have b': "b' =
      (e_append b (list_encode (replicate (y - e_length b) 0 @ [1 - the (φ ?i y)])))"
    using assms y nxt_converg prod_encode_eq by auto
  then show ?thesis using e_length_append by auto
qed

text ‹The next function computes the prefixes after each iteration of
the process @{term r_next} when started with the list $[j]$.›

definition r_prefixes :: recf where
  "r_prefixes  Pr 1 r_singleton_encode (Cn 3 r_next [Id 3 1])"

lemma r_prefixes_recfn [simp]: "recfn 2 r_prefixes"
  unfolding r_prefixes_def by (simp add: Let_def)

abbreviation prefixes :: partial2 where
  "prefixes t j  eval r_prefixes [t, j]"

lemma prefixes_at_0: "prefixes 0 j ↓= list_encode [j]"
  unfolding r_prefixes_def by simp

lemma prefixes_at_Suc:
  assumes "prefixes t j " (is "?b ")
  shows "prefixes (Suc t) j = nxt (the ?b)"
  using r_prefixes_def assms by auto

lemma prefixes_at_Suc':
  assumes "prefixes t j ↓= b"
  shows "prefixes (Suc t) j = nxt b"
  using r_prefixes_def assms by auto

lemma prefixes_prod_encode:
  assumes "prefixes t j "
  obtains b where "prefixes t j ↓= b"
  using assms surj_prod_encode by force

lemma prefixes_converg_le:
  assumes "prefixes t j " and "t'  t"
  shows "prefixes t' j "
  using r_prefixes_def assms eval_Pr_converg_le[of 1 _ _ "[j]"]
  by simp

lemma prefixes_diverg_add:
  assumes "prefixes t j "
  shows "prefixes (t + d) j "
  using r_prefixes_def assms eval_Pr_diverg_add[of 1 _ _ "[j]"]
  by simp

text ‹Many properties of @{term r_prefixes} can be derived from similar
properties of @{term r_next}.›

lemma prefixes_length:
  assumes "prefixes t j ↓= b"
  shows "e_length b > t"
proof (insert assms, induction t arbitrary: b)
  case 0
  then show ?case using prefixes_at_0 prod_encode_eq by auto
next
  case (Suc t)
  then have "prefixes t j "
    using prefixes_converg_le Suc_n_not_le_n nat_le_linear by blast
  then obtain b' where b': "prefixes t j ↓= b'"
    using prefixes_prod_encode by blast
  with Suc have "e_length b' > t" by simp
  have "prefixes (Suc t) j = nxt b'"
    using b' prefixes_at_Suc' by simp
  with Suc have "nxt b' ↓= b" by simp
  then have "e_length b' < e_length b"
    using nxt_monotone by simp
  then show ?case using e_length b' > t by simp
qed

lemma prefixes_monotone:
  assumes "prefixes t j ↓= b" and "prefixes (t + d) j ↓= b'"
  shows "e_length b  e_length b'"
proof (insert assms, induction d arbitrary: b')
  case 0
  then show ?case using prod_encode_eq by simp
next
  case (Suc d)
  moreover have "t + d  t + Suc d" by simp
  ultimately have "prefixes (t + d) j "
    using prefixes_converg_le by blast
  then obtain b'' where b'': "prefixes (t + d) j ↓= b''"
    using prefixes_prod_encode by blast
  with Suc have "prefixes (t + Suc d) j = nxt b''"
    by (simp add: prefixes_at_Suc')
  with Suc have "nxt b'' ↓= b'" by simp
  then show ?case using nxt_monotone Suc b'' by fastforce
qed

lemma prefixes_stable:
  assumes "prefixes t j ↓= b" and "prefixes (t + d) j ↓= b'"
  shows "x<e_length b. e_nth b x = e_nth b' x"
proof (insert assms, induction d arbitrary: b')
  case 0
  then show ?case using prod_encode_eq by simp
next
  case (Suc d)
  moreover have "t + d  t + Suc d" by simp
  ultimately have "prefixes (t + d) j "
    using prefixes_converg_le by blast
  then obtain b'' where b'': "prefixes (t + d) j ↓= b''"
    using prefixes_prod_encode by blast
  with Suc have "prefixes (t + Suc d) j = nxt b''"
    by (simp add: prefixes_at_Suc')
  with Suc have b': "nxt b'' ↓= b'" by simp
  show "x<e_length b. e_nth b x = e_nth b' x"
  proof (rule allI, rule impI)
    fix x assume x: "x < e_length b"
    then have "e_nth b x = e_nth b'' x"
      using Suc b'' by simp
    moreover have "x  e_length b''"
      using x prefixes_monotone b'' Suc by fastforce
    ultimately show "e_nth b x = e_nth b' x"
      using b'' nxt_stable Suc b' prefixes_monotone x
      by (metis leD le_neq_implies_less)
  qed
qed

lemma prefixes_tl_only_01:
  assumes "prefixes t j ↓= b"
  shows "x>0. e_nth b x = 0  e_nth b x = 1"
proof (insert assms, induction t arbitrary: b)
  case 0
  then show ?case using prefixes_at_0 prod_encode_eq by auto
next
  case (Suc t)
  then have "prefixes t j "
    using prefixes_converg_le Suc_n_not_le_n nat_le_linear by blast
  then obtain b' where b': "prefixes t j ↓= b'"
    using prefixes_prod_encode by blast
  show "x>0. e_nth b x = 0  e_nth b x = 1"
  proof (rule allI, rule impI)
    fix x :: nat
    assume x: "x > 0"
    show "e_nth b x = 0  e_nth b x = 1"
    proof (cases "x < e_length b'")
      case True
      then show ?thesis
        using Suc b' prefixes_at_Suc' nxt_stable x by metis
    next
      case False
      then show ?thesis
        using Suc.prems b' prefixes_at_Suc' nxt_append_01 by auto
    qed
  qed
qed

lemma prefixes_hd:
  assumes "prefixes t j ↓= b"
  shows "e_nth b 0 = j"
proof -
  obtain b' where b': "prefixes 0 j ↓= b'"
    by (simp add: prefixes_at_0)
  then have "b' = list_encode [j]"
    by (simp add: prod_encode_eq prefixes_at_0)
  then have "e_nth b' 0 = j" by simp
  then show "e_nth b 0 = j"
    using assms prefixes_stable[OF b', of t b] prefixes_length[OF b'] by simp
qed

lemma prefixes_nontotal_hyp:
  assumes "prefixes t j ↓= b"
    and "prefixes (Suc t) j "
    and "s b ↓= i"
  shows "x. φ i x "
  using nxt_nontotal_hyp[OF _ assms(3)] assms(2) prefixes_at_Suc'[OF assms(1)] by simp

text ‹We now consider the two cases from the proof sketch.›

abbreviation "case_two j  t. prefixes t j "

abbreviation "case_one j  ¬ case_two j"

text ‹In Case~2 there is a maximum convergent iteration because
iteration 0 converges.›

lemma case_two:
  assumes "case_two j"
  shows "t. (t't. prefixes t' j )  (t'>t. prefixes t' j )"
proof -
  let ?P = "λt. prefixes t j "
  define t0 where "t0 = Least ?P"
  then have "?P t0"
    using assms LeastI_ex[of ?P] by simp
  then have diverg: "?P t" if "t  t0" for t
    using prefixes_converg_le that by blast
  from t0_def have converg: "¬ ?P t" if "t < t0" for t
    using Least_le[of ?P] that not_less by blast
  have "t0 > 0"
  proof (rule ccontr)
    assume "¬ 0 < t0"
    then have "t0 = 0" by simp
    with ?P t0 prefixes_at_0 show False by simp
  qed
  let ?t = "t0 - 1"
  have "t'?t. prefixes t' j "
    using converg 0 < t0 by auto
  moreover have "t'>?t. prefixes t' j "
    using diverg by simp
  ultimately show ?thesis by auto
qed

text ‹Having completed the modelling of the process, we can now define
the functions $\psi_j$ it computes. The value $\psi_j(x)$ is computed by
running @{term r_prefixes} until the prefix is longer than $x$ and then
taking the $x$-th element of the prefix.›

definition "r_psi 
  let f = Cn 3 r_less [Id 3 2, Cn 3 r_length [Cn 3 r_prefixes [Id 3 0, Id 3 1]]]
  in Cn 2 r_nth [Cn 2 r_prefixes [Mn 2 f, Id 2 0], Id 2 1]"

lemma r_psi_recfn: "recfn 2 r_psi"
  unfolding r_psi_def by simp

abbreviation psi :: partial2 (ψ) where
  "ψ j x  eval r_psi [j, x]"

lemma psi_in_P2: "ψ  𝒫2"
  using r_psi_recfn by auto

text ‹The values of @{term "ψ"} can be read off the prefixes.›

lemma psi_eq_nth_prefix:
  assumes "prefixes t j ↓= b" and "e_length b > x"
  shows "ψ j x ↓= e_nth b x"
proof -
  let ?f = "Cn 3 r_less [Id 3 2, Cn 3 r_length [Cn 3 r_prefixes [Id 3 0, Id 3 1]]]"
  let ?P = "λt. prefixes t j   e_length (the (prefixes t j)) > x"
  from assms have ex_t: "t. ?P t" by auto
  define t0 where "t0 = Least ?P"
  then have "?P t0"
    using LeastI_ex[OF ex_t] by simp
  from ex_t have not_P: "¬ ?P t" if "t < t0" for t
    using ex_t that Least_le[of ?P] not_le t0_def by auto

  have "?P t" using assms by simp
  with not_P have "t0  t" using leI by blast
  then obtain b0 where b0: "prefixes t0 j ↓= b0"
    using assms(1) prefixes_converg_le by blast

  have "eval ?f [t0, j, x] ↓= 0"
  proof -
    have "eval (Cn 3 r_prefixes [Id 3 0, Id 3 1]) [t0, j, x] ↓= b0"
      using b0 by simp
    then show ?thesis using ?P t0 by simp
  qed
  moreover have "eval ?f [t, j, x] ↓≠ 0" if "t < t0" for t
  proof -
    obtain bt where bt: "prefixes t j ↓= bt"
      using prefixes_converg_le[of t0 j t] b0 t < t0 by auto
    moreover have "¬ ?P t"
      using that not_P by simp
    ultimately have "e_length bt  x" by simp
    moreover have "eval (Cn 3 r_prefixes [Id 3 0, Id 3 1]) [t, j, x] ↓= bt"
      using bt by simp
    ultimately show ?thesis by simp
  qed
  ultimately have "eval (Mn 2 ?f) [j, x] ↓= t0"
    using eval_Mn_convergI[of 2 ?f "[j, x]" t0] by simp
  then have "ψ j x ↓= e_nth b0 x"
    unfolding r_psi_def using b0 by simp
  then show ?thesis
    using t0  t assms(1) prefixes_stable[of t0 j b0 "t - t0" b] b0 ?P t0
    by simp
qed

lemma psi_converg_imp_prefix:
  assumes "ψ j x "
  shows "t b. prefixes t j ↓= b  e_length b > x"
proof -
  let ?f = "Cn 3 r_less [Id 3 2, Cn 3 r_length [Cn 3 r_prefixes [Id 3 0, Id 3 1]]]"
  have "eval (Mn 2 ?f) [j, x] "
  proof (rule ccontr)
    assume "¬ eval (Mn 2 ?f) [j, x] "
    then have "eval (Mn 2 ?f) [j, x] " by simp
    then have "ψ j x "
      unfolding r_psi_def by simp
    then show False
      using assms by simp
  qed
  then obtain t where t: "eval (Mn 2 ?f) [j, x] ↓= t"
    by blast
  have "recfn 2 (Mn 2 ?f)" by simp
  then have f_zero: "eval ?f [t, j, x] ↓= 0"
    using eval_Mn_convergE[OF _ t]
    by (metis (no_types, lifting) One_nat_def Suc_1 length_Cons list.size(3))
  have "prefixes t j "
  proof (rule ccontr)
    assume "¬ prefixes t j "
    then have "prefixes t j " by simp
    then have "eval ?f [t, j, x] " by simp
    with f_zero show False by simp
  qed
  then obtain b' where b': "prefixes t j ↓= b'" by auto
  moreover have "e_length b' > x"
  proof (rule ccontr)
    assume "¬ e_length b' > x"
    then have "eval ?f [t, j, x] ↓= 1"
      using b' by simp
    with f_zero show False by simp
  qed
  ultimately show ?thesis by auto
qed

lemma psi_converg_imp_prefix':
  assumes "ψ j x "
  shows "t b. prefixes t j ↓= b  e_length b > x  ψ j x ↓= e_nth b x"
  using psi_converg_imp_prefix[OF assms] psi_eq_nth_prefix by blast

text ‹In both Case~1 and~2, $\psi_j$ starts with $j$.›

lemma psi_at_0: "ψ j 0 ↓= j"
  using prefixes_hd prefixes_length psi_eq_nth_prefix prefixes_at_0 by fastforce

text ‹In Case~1, $\psi_j$ is total and made up of $j$ followed by zeros
and ones, just as required by the definition of $V_1$.›

lemma case_one_psi_total:
  assumes "case_one j" and "x > 0"
  shows "ψ j x ↓= 0  ψ j x ↓= 1"
proof -
  obtain b where b: "prefixes x j ↓= b"
    using assms(1) by auto
  then have "e_length b > x"
    using prefixes_length by simp
  then have "ψ j x ↓= e_nth b x"
    using b psi_eq_nth_prefix by simp
  moreover have "e_nth b x = 0  e_nth b x = 1"
    using prefixes_tl_only_01[OF b] assms(2) by simp
  ultimately show "ψ j x ↓= 0  ψ j x ↓= 1"
    by simp
qed

text ‹In Case~2, $\psi_j$ is defined only for a prefix starting with
$j$ and continuing with zeros and ones. This prefix corresponds to $ja$ from
the definition of $V_2$.›

lemma case_two_psi_only_prefix:
  assumes "case_two j"
  shows "y. (x. 0 < x  x < y  ψ j x ↓= 0  ψ j x ↓= 1) 
                (x  y. ψ j x )"
proof -
  obtain t where
    t_le: "t't. prefixes t' j " and
    t_gr: "t'>t. prefixes t' j "
    using assms case_two by blast
  then obtain b where b: "prefixes t j ↓= b"
    by auto
  let ?y = "e_length b"
  have "ψ j x ↓= 0  ψ j x ↓= 1" if "x > 0  x < ?y" for x
    using t_le b that by (metis prefixes_tl_only_01 psi_eq_nth_prefix)
  moreover have "ψ j x " if "x  ?y" for x
  proof (rule ccontr)
    assume "ψ j x "
    then obtain t' b' where t': "prefixes t' j ↓= b'" and "e_length b' > x"
      using psi_converg_imp_prefix by blast
    then have "e_length b' > ?y"
      using that by simp
    with t' have "t' > t"
      using prefixes_monotone b by (metis add_diff_inverse_nat leD)
    with t' t_gr show False by simp
  qed
  ultimately show ?thesis by auto
qed

definition longest_prefix :: "nat  nat" where
  "longest_prefix j  THE y. (x<y. ψ j x )  (xy. ψ j x )"

lemma longest_prefix:
  assumes "case_two j" and "z = longest_prefix j"
  shows "(x<z. ψ j x )  (xz. ψ j x )"
proof -
  let ?P = "λz. (x<z. ψ j x )  (xz. ψ j x )"
  obtain y where y:
    "x. 0 < x  x < y  ψ j x ↓= 0  ψ j x ↓= 1"
    "xy. ψ j x "
    using case_two_psi_only_prefix[OF assms(1)] by auto
  have "?P (THE z. ?P z)"
  proof (rule theI[of ?P y])
    show "?P y"
    proof
      show "x<y. ψ j x "
      proof (rule allI, rule impI)
        fix x assume "x < y"
        show "ψ j x "
        proof (cases "x = 0")
          case True
          then show ?thesis using psi_at_0 by simp
        next
          case False
          then show ?thesis using y(1) x < y by auto
        qed
      qed
      show "xy. ψ j x " using y(2) by simp
    qed
    show "z = y" if "?P z" for z
    proof (rule ccontr, cases "z < y")
      case True
      moreover assume "z  y"
      ultimately show False
        using that ?P y by auto
    next
      case False
      moreover assume "z  y"
      then show False
        using that ?P y y(2) by (meson linorder_cases order_refl)
    qed
  qed
  then have "(x<(THE z. ?P z). ψ j x )  (x(THE z. ?P z). ψ j x )"
    by blast
  moreover have "longest_prefix j = (THE z. ?P z)"
    unfolding longest_prefix_def by simp
  ultimately show ?thesis using assms(2) by metis
qed

lemma case_two_psi_longest_prefix:
  assumes "case_two j" and "y = longest_prefix j"
  shows "(x. 0 < x  x < y  ψ j x ↓= 0  ψ j x ↓= 1) 
    (x  y. ψ j x )"
  using assms longest_prefix case_two_psi_only_prefix
  by (metis prefixes_tl_only_01 psi_converg_imp_prefix')

text ‹The prefix cannot be empty because the process starts with prefix $[j]$.›

lemma longest_prefix_gr_0:
  assumes "case_two j"
  shows "longest_prefix j > 0"
  using assms case_two_psi_longest_prefix psi_at_0 by force

lemma psi_not_divergent_init:
  assumes "prefixes t j ↓= b"
  shows "(ψ j)  (e_length b - 1) = b"
proof (intro initI)
  show "0 < e_length b"
    using assms prefixes_length by fastforce
  show "ψ j x ↓= e_nth b x" if "x < e_length b" for x
    using that assms psi_eq_nth_prefix by simp
qed

text ‹In Case~2, the strategy $S$ outputs a non-total hypothesis on
some prefix of $\psi_j$.›

lemma case_two_nontotal_hyp:
  assumes "case_two j"
  shows "n<longest_prefix j. ¬ total1 (φ (the (s ((ψ j)  n))))"
proof -
  obtain t where "t't. prefixes t' j " and t_gr: "t'>t. prefixes t' j "
    using assms case_two by blast
  then obtain b where b: "prefixes t j ↓= b"
    by auto
  moreover obtain i where i: "s b ↓= i"
    using eval_rs by fastforce
  moreover have div: "prefixes (Suc t) j "
    using t_gr by simp
  ultimately have "x. φ i x "
    using prefixes_nontotal_hyp by simp
  then obtain x where "φ i x " by auto
  moreover have init: "ψ j  (e_length b - 1) = b" (is "_  ?n = b")
    using psi_not_divergent_init[OF b] by simp
  ultimately have "φ (the (s (ψ j  ?n))) x "
    using i by simp
  then have "¬ total1 (φ (the (s (ψ j  ?n))))"
    by auto
  moreover have "?n < longest_prefix j"
    using case_two_psi_longest_prefix init b div psi_eq_nth_prefix
    by (metis length_init lessI not_le_imp_less option.simps(3))
  ultimately show ?thesis by auto
qed

text ‹Consequently, in Case~2 the strategy does not TOTAL-learn
any function starting with the longest prefix of $\psi_j$.›

lemma case_two_not_learn:
  assumes "case_two j"
    and "f  "
    and "x. x < longest_prefix j  f x = ψ j x"
  shows "¬ learn_total φ {f} s"
proof -
  obtain n where n:
    "n < longest_prefix j"
    "¬ total1 (φ (the (s (ψ j  n))))"
    using case_two_nontotal_hyp[OF assms(1)] by auto
  have "f  n = ψ j  n"
    using assms(3) n(1) by (intro init_eqI) auto
  with n(2) show ?thesis by (metis R1_imp_total1 learn_totalE(3) singletonI)
qed

text ‹In Case~1 the strategy outputs a wrong hypothesis
on infinitely many prefixes of $\psi_j$ and thus does not
learn $\psi_j$ in the limit, much less in the sense of TOTAL.›

lemma case_one_wrong_hyp:
  assumes "case_one j"
  shows "n>k. φ (the (s ((ψ j)  n)))  ψ j"
proof -
  have all_t: "t. prefixes t j "
    using assms by simp
  then obtain b where b: "prefixes (Suc k) j ↓= b"
    by auto
  then have length: "e_length b > Suc k"
    using prefixes_length by simp
  then have init: "ψ j  (e_length b - 1) = b"
    using psi_not_divergent_init b by simp
  obtain i where i: "s b ↓= i"
    using eval_rs by fastforce
  from all_t obtain b' where b': "prefixes (Suc (Suc k)) j ↓= b'"
    by auto
  then have "ψ j  (e_length b' - 1) = b'"
    using psi_not_divergent_init by simp
  moreover have "y<e_length b'. φ i y ↓≠ e_nth b' y"
    using nxt_wrong_hyp b b' i prefixes_at_Suc by auto
  ultimately have "y<e_length b'. φ i y  ψ j y"
    using b' psi_eq_nth_prefix by auto
  then have "φ i  ψ j" by auto
  then show ?thesis
    using init length i by (metis Suc_less_eq length_init option.sel)
qed

lemma case_one_not_learn:
  assumes "case_one j"
  shows "¬ learn_lim φ {ψ j} s"
proof (rule infinite_hyp_wrong_not_Lim[of "ψ j"])
  show "ψ j  {ψ j}" by simp
  show "n. m>n. φ (the (s (ψ j  m)))  ψ j"
    using case_one_wrong_hyp[OF assms] by simp
qed

lemma case_one_not_learn_V:
  assumes "case_one j" and "j  2" and "φ j = ψ j"
  shows "¬ learn_lim φ V_constotal s"
proof -
  have "ψ j  V_constotal_1"
  proof -
    define p where "p = (λx. (ψ j) (x + 1))"
    have "p  01"
    proof -
      from p_def have "p  𝒫"
        using skip_P1[of "ψ j" 1] psi_in_P2 P2_proj_P1 by blast
      moreover have "p x ↓= 0  p x ↓= 1" for x
        using p_def assms(1) case_one_psi_total by auto
      moreover from this have "total1 p" by fast
      ultimately show ?thesis using RPred1_def by auto
    qed
    moreover have "ψ j = [j]  p"
      by (intro prepend_eqI, simp add: psi_at_0, simp add: p_def)
    ultimately show ?thesis using assms(2,3) V_constotal_1_def by blast
  qed
  then have "ψ j  V_constotal" using V_constotal_def by auto
  moreover have "¬ learn_lim φ {ψ j} s"
    using case_one_not_learn assms(1) by simp
  ultimately show ?thesis using learn_lim_closed_subseteq by auto
qed

text ‹The next lemma embodies the construction of $\chi$ followed by
the application of Kleene's fixed-point theorem as described in the
proof sketch.›

lemma goedel_after_prefixes:
  fixes vs :: "nat list" and m :: nat
  shows "nm. φ n = vs @ [n]  0"
proof -
  define f :: partial1 where "f  vs  0"
  then have "f  "
    using almost0_in_R1 by auto
  then obtain n where n:
    "n  m"
    "φ n = (λx. if x = length vs then Some n else f x)"
    using goedel_at[of f m "length vs"] by auto
  moreover have "φ n x = (vs @ [n]  0) x" for x
  proof -
    consider "x < length vs" | "x = length vs" | "x > length vs"
      by linarith
    then show ?thesis
      using n f_def by (cases) (auto simp add: prepend_associative)
  qed
  ultimately show ?thesis by blast
qed

text ‹If Case~2 holds for a $j\geq 2$ with $\varphi_j = \psi_j$, that
is, if $\psi_j\in V_1$, then there is a function in $V$, namely $\psi_j$, on
which $S$ fails. Therefore $S$ does not learn $V$.›

lemma case_two_not_learn_V:
  assumes "case_two j" and "j  2" and "φ j = ψ j"
  shows "¬ learn_total φ V_constotal s"
proof -
  define z where "z = longest_prefix j"
  then have "z > 0"
    using longest_prefix_gr_0[OF assms(1)] by simp
  define vs where "vs = prefix (ψ j) (z - 1)"
  then have "vs ! 0 = j"
    using psi_at_0 z > 0 by simp
  define a where "a = tl vs"
  then have vs: "vs = j # a"
    using vs_def vs ! 0 = j
    by (metis length_Suc_conv length_prefix list.sel(3) nth_Cons_0)
  obtain k where k: "k  2" and phi_k: "φ k = j # a @ [k]  0"
    using goedel_after_prefixes[of 2 "j # a"] by auto
  have phi_j: "φ j = j # a   "
  proof (rule prepend_eqI)
    show "x. x < length (j # a)  φ j x ↓= (j # a) ! x"
      using assms(1,3) vs vs_def 0 < z
        length_prefix[of "ψ j" "z - 1"]
        prefix_nth[of _ _ "ψ j"]
        psi_at_0[of j]
        case_two_psi_longest_prefix[OF _ z_def]
        longest_prefix[OF _ z_def]
      by (metis One_nat_def Suc_pred option.collapse)
    show "x. φ j (length (j # a) + x) "
      using assms(3) vs_def
      by (simp add: vs assms(1) case_two_psi_longest_prefix z_def)
  qed
  moreover have "φ k  V_constotal_2"
  proof (intro V_constotal_2I[of _ j a k])
    show "φ k = j # a @ [k]  0"
      using phi_k .
    show "2  j"
      using 2  j .
    show "2  k"
      using 2  k .
    show "i<length a. a ! i  1"
    proof (rule allI, rule impI)
      fix i assume i: "i < length a"
      then have "Suc i < z"
        using z_def vs_def length_prefix 0 < z vs
        by (metis One_nat_def Suc_mono Suc_pred length_Cons)
      have "a ! i = vs ! (Suc i)"
        using vs by simp
      also have "... = the (ψ j (Suc i))"
        using vs_def vs i length_Cons length_prefix prefix_nth
        by (metis Suc_mono)
      finally show "a ! i  1"
        using case_two_psi_longest_prefix Suc i < z z_def
        by (metis assms(1) less_or_eq_imp_le not_le_imp_less not_one_less_zero
          option.sel zero_less_Suc)
    qed
  qed (auto simp add: phi_j)
  then have "φ k  V_constotal"
    using V_constotal_def by auto
  moreover have "¬ learn_total φ {φ k} s"
  proof -
    have "φ k  "
      by (simp add: phi_k almost0_in_R1)
    moreover have "x. x < longest_prefix j  φ k x = ψ j x"
      using phi_k vs_def z_def length_prefix phi_j prepend_associative prepend_at_less
      by (metis One_nat_def Suc_pred 0 < z vs = j # a append_Cons assms(3))
    ultimately show ?thesis
      using case_two_not_learn[OF assms(1)] by simp
  qed
  ultimately show "¬ learn_total φ V_constotal s"
    using learn_total_closed_subseteq by auto
qed

text ‹The strategy $S$ does not learn $V$ in either case.›

lemma not_learn_total_V: "¬ learn_total φ V_constotal s"
proof -
  obtain j where "j  2" "φ j = ψ j"
    using kleene_fixed_point psi_in_P2 by auto
  then show ?thesis
    using case_one_not_learn_V learn_total_def case_two_not_learn_V
    by (cases "case_two j") auto
qed

end


lemma V_not_in_TOTAL: "V_constotal  TOTAL"
proof (rule ccontr)
  assume "¬ V_constotal  TOTAL"
  then have "V_constotal  TOTAL" by simp
  then have "V_constotal  TOTAL_wrt φ"
    by (simp add: TOTAL_wrt_phi_eq_TOTAL)
  then obtain s where "learn_total φ V_constotal s"
    using TOTAL_wrt_def by auto
  then obtain s' where s': "s'  " "learn_total φ V_constotal s'"
    using lemma_R_for_TOTAL_simple by blast
  then interpret total_cons s'
    by (simp add: total_cons_def)
  have "¬ learn_total φ V_constotal s'"
    by (simp add: not_learn_total_V)
  with s'(2) show False by simp
qed

lemma TOTAL_neq_CONS: "TOTAL  CONS"
  using V_not_in_TOTAL V_in_CONS CONS_def by auto

text ‹The main result of this section:›

theorem TOTAL_subset_CONS: "TOTAL  CONS"
  using TOTAL_subseteq_CONS TOTAL_neq_CONS by simp

end