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(* Author: Andreas Lochbihler, Digital Asset *)
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theory Code_Lazy_Demo imports
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"HOL-Library.Code_Lazy"
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"HOL-Library.Debug"
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"HOL-Library.RBT_Impl"
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begin
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text \<open>This theory demonstrates the use of the @{theory "HOL-Library.Code_Lazy"} theory.\<close>
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section \<open>Streams\<close>
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text \<open>Lazy evaluation for streams\<close>
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codatatype 'a stream =
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SCons (shd: 'a) (stl: "'a stream") (infixr "##" 65)
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primcorec up :: "nat \<Rightarrow> nat stream" where
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"up n = n ## up (n + 1)"
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primrec stake :: "nat \<Rightarrow> 'a stream \<Rightarrow> 'a list" where
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"stake 0 xs = []"
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| "stake (Suc n) xs = shd xs # stake n (stl xs)"
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code_thms up stake \<comment> \<open>The original code equations\<close>
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code_lazy_type stream
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code_thms up stake \<comment> \<open>The lazified code equations\<close>
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value "stake 5 (up 3)"
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section \<open>Finite lazy lists\<close>
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text \<open>Lazy types need not be infinite. We can also have lazy types that are finite.\<close>
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datatype 'a llist
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= LNil ("\<^bold>\<lbrakk>\<^bold>\<rbrakk>")
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| LCons (lhd: 'a) (ltl: "'a llist") (infixr "###" 65)
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syntax "_llist" :: "args => 'a list" ("\<^bold>\<lbrakk>(_)\<^bold>\<rbrakk>")
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translations
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"\<^bold>\<lbrakk>x, xs\<^bold>\<rbrakk>" == "x###\<^bold>\<lbrakk>xs\<^bold>\<rbrakk>"
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"\<^bold>\<lbrakk>x\<^bold>\<rbrakk>" == "x###\<^bold>\<lbrakk>\<^bold>\<rbrakk>"
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fun lnth :: "nat \<Rightarrow> 'a llist \<Rightarrow> 'a" where
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"lnth 0 (x ### xs) = x"
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| "lnth (Suc n) (x ### xs) = lnth n xs"
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definition llist :: "nat llist" where
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"llist = \<^bold>\<lbrakk>1, 2, 3, hd [], 4\<^bold>\<rbrakk>"
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code_lazy_type llist
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value [code] "llist"
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value [code] "lnth 2 llist"
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value [code] "let x = lnth 2 llist in (x, llist)"
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fun lfilter :: "('a \<Rightarrow> bool) \<Rightarrow> 'a llist \<Rightarrow> 'a llist" where
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"lfilter P \<^bold>\<lbrakk>\<^bold>\<rbrakk> = \<^bold>\<lbrakk>\<^bold>\<rbrakk>"
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| "lfilter P (x ### xs) =
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(if P x then x ### lfilter P xs else lfilter P xs)"
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export_code lfilter in SML
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value [code] "lfilter odd llist"
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value [code] "lhd (lfilter odd llist)"
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section \<open>Iterator for red-black trees\<close>
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text \<open>Thanks to laziness, we do not need to program a complicated iterator for a tree.
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A conversion function to lazy lists is enough.\<close>
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primrec lappend :: "'a llist \<Rightarrow> 'a llist \<Rightarrow> 'a llist"
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(infixr "@@" 65) where
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"\<^bold>\<lbrakk>\<^bold>\<rbrakk> @@ ys = ys"
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| "(x ### xs) @@ ys = x ### (xs @@ ys)"
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primrec rbt_iterator :: "('a, 'b) rbt \<Rightarrow> ('a \<times> 'b) llist" where
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"rbt_iterator rbt.Empty = \<^bold>\<lbrakk>\<^bold>\<rbrakk>"
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| "rbt_iterator (Branch _ l k v r) =
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(let _ = Debug.flush (STR ''tick'') in
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rbt_iterator l @@ (k, v) ### rbt_iterator r)"
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definition tree :: "(nat, unit) rbt"
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where "tree = fold (\<lambda>k. rbt_insert k ()) [0..<100] rbt.Empty"
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definition find_min :: "('a :: linorder, 'b) rbt \<Rightarrow> ('a \<times> 'b) option" where
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"find_min rbt =
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(case rbt_iterator rbt of \<^bold>\<lbrakk>\<^bold>\<rbrakk> \<Rightarrow> None
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| kv ### _ \<Rightarrow> Some kv)"
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value "find_min tree" \<comment> \<open>Observe that @{const rbt_iterator} is evaluated only for going down
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to the first leaf, not for the whole tree (as seen by the ticks).\<close>
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text \<open>With strict lists, the whole tree is converted into a list.\<close>
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deactivate_lazy_type llist
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value "find_min tree"
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activate_lazy_type llist
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section \<open>Branching datatypes\<close>
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datatype tree
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= L ("\<spadesuit>")
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| Node tree tree (infix "\<triangle>" 900)
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notation (output) Node ("\<triangle>(//\<^bold>l: _//\<^bold>r: _)")
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code_lazy_type tree
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fun mk_tree :: "nat \<Rightarrow> tree" where mk_tree_0:
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"mk_tree 0 = \<spadesuit>"
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| "mk_tree (Suc n) = (let t = mk_tree n in t \<triangle> t)"
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declare mk_tree.simps [code]
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code_thms mk_tree
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function subtree :: "bool list \<Rightarrow> tree \<Rightarrow> tree" where
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"subtree [] t = t"
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| "subtree (True # p) (l \<triangle> r) = subtree p l"
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| "subtree (False # p) (l \<triangle> r) = subtree p r"
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| "subtree _ \<spadesuit> = \<spadesuit>"
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by pat_completeness auto
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termination by lexicographic_order
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value [code] "mk_tree 10"
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value [code] "let t = mk_tree 10; _ = subtree [True, True, False, False] t in t"
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\<comment> \<open>Since @{const mk_tree} shares the two subtrees of a node thanks to the let binding,
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digging into one subtree spreads to the whole tree.\<close>
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value [code] "let t = mk_tree 3; _ = subtree [True, True, False, False] t in t"
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lemma mk_tree_Suc_debug [code]: \<comment> \<open>Make the evaluation visible with tracing.\<close>
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"mk_tree (Suc n) =
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(let _ = Debug.flush (STR ''tick''); t = mk_tree n in t \<triangle> t)"
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by simp
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value [code] "mk_tree 10"
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\<comment> \<open>The recursive call to @{const mk_tree} is not guarded by a lazy constructor,
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so all the suspensions are built up immediately.\<close>
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lemma mk_tree_Suc [code]: "mk_tree (Suc n) = mk_tree n \<triangle> mk_tree n"
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\<comment> \<open>In this code equation, there is no sharing and the recursive calls are guarded by a constructor.\<close>
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by(simp add: Let_def)
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value [code] "mk_tree 10"
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value [code] "let t = mk_tree 10; _ = subtree [True, True, False, False] t in t"
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lemma mk_tree_Suc_debug' [code]:
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"mk_tree (Suc n) = (let _ = Debug.flush (STR ''tick'') in mk_tree n \<triangle> mk_tree n)"
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by(simp add: Let_def)
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value [code] "mk_tree 10" \<comment> \<open>Only one tick thanks to the guarding constructor\<close>
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value [code] "let t = mk_tree 10; _ = subtree [True, True, False, False] t in t"
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value [code] "let t = mk_tree 3; _ = subtree [True, True, False, False] t in t"
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section \<open>Pattern matching elimination\<close>
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text \<open>The pattern matching elimination handles deep pattern matches and overlapping equations
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and only eliminates necessary pattern matches.\<close>
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function crazy :: "nat llist llist \<Rightarrow> tree \<Rightarrow> bool \<Rightarrow> unit" where
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"crazy (\<^bold>\<lbrakk>0\<^bold>\<rbrakk> ### xs) _ _ = Debug.flush (1 :: integer)"
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| "crazy xs \<spadesuit> True = Debug.flush (2 :: integer)"
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| "crazy xs t b = Debug.flush (3 :: integer)"
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by pat_completeness auto
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termination by lexicographic_order
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code_thms crazy
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end |