Theory RBT_Mapping

theory RBT_Mapping
imports RBT Mapping
(*  Title:      HOL/Library/RBT_Mapping.thy
    Author:     Florian Haftmann and Ondrej Kuncar

section ‹Implementation of mappings with Red-Black Trees›

theory RBT_Mapping
imports RBT Mapping

subsection ‹Implementation of mappings›

context includes rbt.lifting begin
lift_definition Mapping :: "('a::linorder, 'b) rbt ⇒ ('a, 'b) mapping" is RBT.lookup .

code_datatype Mapping

context includes rbt.lifting begin

lemma lookup_Mapping [simp, code]:
  "Mapping.lookup (Mapping t) = RBT.lookup t"
   by (transfer fixing: t) rule

lemma empty_Mapping [code]: "Mapping.empty = Mapping RBT.empty"
proof -
  note RBT.empty.transfer[transfer_rule del]
  show ?thesis by transfer simp

lemma is_empty_Mapping [code]:
  "Mapping.is_empty (Mapping t) ⟷ RBT.is_empty t"
  unfolding is_empty_def by (transfer fixing: t) simp

lemma insert_Mapping [code]:
  "Mapping.update k v (Mapping t) = Mapping (RBT.insert k v t)"
  by (transfer fixing: t) simp

lemma delete_Mapping [code]:
  "Mapping.delete k (Mapping t) = Mapping (RBT.delete k t)"
  by (transfer fixing: t) simp

lemma map_entry_Mapping [code]:
  "Mapping.map_entry k f (Mapping t) = Mapping (RBT.map_entry k f t)"
  apply (transfer fixing: t)
  apply (case_tac "RBT.lookup t k")
   apply auto

lemma keys_Mapping [code]:
  "Mapping.keys (Mapping t) = set (RBT.keys t)"
by (transfer fixing: t) (simp add: lookup_keys)

lemma ordered_keys_Mapping [code]:
  "Mapping.ordered_keys (Mapping t) = RBT.keys t"
unfolding ordered_keys_def 
by (transfer fixing: t) (auto simp add: lookup_keys intro: sorted_distinct_set_unique)

lemma Mapping_size_card_keys: (*FIXME*)
  "Mapping.size m = card (Mapping.keys m)"
unfolding size_def by transfer simp

lemma size_Mapping [code]:
  "Mapping.size (Mapping t) = length (RBT.keys t)"
unfolding size_def
by (transfer fixing: t) (simp add: lookup_keys distinct_card)

  notes RBT.bulkload.transfer[transfer_rule del]

lemma tabulate_Mapping [code]:
  "Mapping.tabulate ks f = Mapping (RBT.bulkload ( (λk. (k, f k)) ks))"
by transfer (simp add: map_of_map_restrict)

lemma bulkload_Mapping [code]:
  "Mapping.bulkload vs = Mapping (RBT.bulkload ( (λn. (n, vs ! n)) [0..<length vs]))"
by transfer (simp add: map_of_map_restrict fun_eq_iff)


lemma map_values_Mapping [code]: 
  "Mapping.map_values f (Mapping t) = Mapping ( f t)"
  by (transfer fixing: t) (auto simp: fun_eq_iff)

lemma filter_Mapping [code]: 
  "Mapping.filter P (Mapping t) = Mapping (RBT.filter P t)"
  by (transfer' fixing: P t) (simp add: RBT.lookup_filter fun_eq_iff)

lemma combine_with_key_Mapping [code]:
  "Mapping.combine_with_key f (Mapping t1) (Mapping t2) =
     Mapping (RBT.combine_with_key f t1 t2)"
  by (transfer fixing: f t1 t2) (simp_all add: fun_eq_iff)

lemma combine_Mapping [code]:
  "Mapping.combine f (Mapping t1) (Mapping t2) =
     Mapping (RBT.combine f t1 t2)"
  by (transfer fixing: f t1 t2) (simp_all add: fun_eq_iff)

lemma equal_Mapping [code]:
  "HOL.equal (Mapping t1) (Mapping t2) ⟷ RBT.entries t1 = RBT.entries t2"
  by (transfer fixing: t1 t2) (simp add: entries_lookup)

lemma [code nbe]:
  "HOL.equal (x :: (_, _) mapping) x ⟷ True"
  by (fact equal_refl)



text ‹
  This theory defines abstract red-black trees as an efficient
  representation of finite maps, backed by the implementation
  in @{theory RBT_Impl}.

subsection ‹Data type and invariant›

text ‹
  The type @{typ "('k, 'v) RBT_Impl.rbt"} denotes red-black trees with
  keys of type @{typ "'k"} and values of type @{typ "'v"}. To function
  properly, the key type musorted belong to the ‹linorder›

  A value @{term t} of this type is a valid red-black tree if it
  satisfies the invariant ‹is_rbt t›.  The abstract type @{typ
  "('k, 'v) rbt"} always obeys this invariant, and for this reason you
  should only use this in our application.  Going back to @{typ "('k,
  'v) RBT_Impl.rbt"} may be necessary in proofs if not yet proven
  properties about the operations must be established.

  The interpretation function @{const "RBT.lookup"} returns the partial
  map represented by a red-black tree:
  @{term_type[display] "RBT.lookup"}

  This function should be used for reasoning about the semantics of the RBT
  operations. Furthermore, it implements the lookup functionality for
  the data structure: It is executable and the lookup is performed in
  $O(\log n)$.  

subsection ‹Operations›

text ‹
  Currently, the following operations are supported:

  @{term_type [display] "RBT.empty"}
  Returns the empty tree. $O(1)$

  @{term_type [display] "RBT.insert"}
  Updates the map at a given position. $O(\log n)$

  @{term_type [display] "RBT.delete"}
  Deletes a map entry at a given position. $O(\log n)$

  @{term_type [display] "RBT.entries"}
  Return a corresponding key-value list for a tree.

  @{term_type [display] "RBT.bulkload"}
  Builds a tree from a key-value list.

  @{term_type [display] "RBT.map_entry"}
  Maps a single entry in a tree.

  @{term_type [display] ""}
  Maps all values in a tree. $O(n)$

  @{term_type [display] "RBT.fold"}
  Folds over all entries in a tree. $O(n)$

subsection ‹Invariant preservation›

text ‹
  @{thm Empty_is_rbt}\hfill(‹Empty_is_rbt›)

  @{thm rbt_insert_is_rbt}\hfill(‹rbt_insert_is_rbt›)

  @{thm rbt_delete_is_rbt}\hfill(‹delete_is_rbt›)

  @{thm rbt_bulkload_is_rbt}\hfill(‹bulkload_is_rbt›)

  @{thm rbt_map_entry_is_rbt}\hfill(‹map_entry_is_rbt›)

  @{thm map_is_rbt}\hfill(‹map_is_rbt›)

  @{thm rbt_union_is_rbt}\hfill(‹union_is_rbt›)

subsection ‹Map Semantics›

text ‹
  @{thm [display] lookup_empty}

  @{thm [display] lookup_insert}

  @{thm [display] lookup_delete}

  @{thm [display] lookup_bulkload}

  @{thm [display] lookup_map}