diff --git a/src/HOL/Data_Structures/Binomial_Heap.thy b/src/HOL/Data_Structures/Binomial_Heap.thy
--- a/src/HOL/Data_Structures/Binomial_Heap.thy
+++ b/src/HOL/Data_Structures/Binomial_Heap.thy
@@ -1,647 +1,647 @@
 (* Author: Peter Lammich
            Tobias Nipkow (tuning)
 *)
 
 section \<open>Binomial Heap\<close>
 
 theory Binomial_Heap
 imports
   "HOL-Library.Pattern_Aliases"
   Complex_Main
   Priority_Queue_Specs
 begin
 
 text \<open>
   We formalize the binomial heap presentation from Okasaki's book.
   We show the functional correctness and complexity of all operations.
 
   The presentation is engineered for simplicity, and most
   proofs are straightforward and automatic.
 \<close>
 
 subsection \<open>Binomial Tree and Heap Datatype\<close>
 
 datatype 'a tree = Node (rank: nat) (root: 'a) (children: "'a tree list")
 
-type_synonym 'a heap = "'a tree list"
+type_synonym 'a trees = "'a tree list"
 
 subsubsection \<open>Multiset of elements\<close>
 
 fun mset_tree :: "'a::linorder tree \<Rightarrow> 'a multiset" where
   "mset_tree (Node _ a ts) = {#a#} + (\<Sum>t\<in>#mset ts. mset_tree t)"
 
-definition mset_heap :: "'a::linorder heap \<Rightarrow> 'a multiset" where
-  "mset_heap ts = (\<Sum>t\<in>#mset ts. mset_tree t)"
+definition mset_trees :: "'a::linorder trees \<Rightarrow> 'a multiset" where
+  "mset_trees ts = (\<Sum>t\<in>#mset ts. mset_tree t)"
 
 lemma mset_tree_simp_alt[simp]:
-  "mset_tree (Node r a ts) = {#a#} + mset_heap ts"
-  unfolding mset_heap_def by auto
+  "mset_tree (Node r a ts) = {#a#} + mset_trees ts"
+  unfolding mset_trees_def by auto
 declare mset_tree.simps[simp del]
 
 lemma mset_tree_nonempty[simp]: "mset_tree t \<noteq> {#}"
 by (cases t) auto
 
-lemma mset_heap_Nil[simp]:
-  "mset_heap [] = {#}"
-by (auto simp: mset_heap_def)
+lemma mset_trees_Nil[simp]:
+  "mset_trees [] = {#}"
+by (auto simp: mset_trees_def)
 
-lemma mset_heap_Cons[simp]: "mset_heap (t#ts) = mset_tree t + mset_heap ts"
-by (auto simp: mset_heap_def)
+lemma mset_trees_Cons[simp]: "mset_trees (t#ts) = mset_tree t + mset_trees ts"
+by (auto simp: mset_trees_def)
 
-lemma mset_heap_empty_iff[simp]: "mset_heap ts = {#} \<longleftrightarrow> ts=[]"
-by (auto simp: mset_heap_def)
+lemma mset_trees_empty_iff[simp]: "mset_trees ts = {#} \<longleftrightarrow> ts=[]"
+by (auto simp: mset_trees_def)
 
 lemma root_in_mset[simp]: "root t \<in># mset_tree t"
 by (cases t) auto
 
-lemma mset_heap_rev_eq[simp]: "mset_heap (rev ts) = mset_heap ts"
-by (auto simp: mset_heap_def)
+lemma mset_trees_rev_eq[simp]: "mset_trees (rev ts) = mset_trees ts"
+by (auto simp: mset_trees_def)
 
 subsubsection \<open>Invariants\<close>
 
 text \<open>Binomial tree\<close>
-fun invar_btree :: "'a::linorder tree \<Rightarrow> bool" where
-"invar_btree (Node r x ts) \<longleftrightarrow>
-   (\<forall>t\<in>set ts. invar_btree t) \<and> map rank ts = rev [0..<r]"
+fun btree :: "'a::linorder tree \<Rightarrow> bool" where
+"btree (Node r x ts) \<longleftrightarrow>
+   (\<forall>t\<in>set ts. btree t) \<and> map rank ts = rev [0..<r]"
 
-text \<open>Ordering (heap) invariant\<close>
-fun invar_otree :: "'a::linorder tree \<Rightarrow> bool" where
-"invar_otree (Node _ x ts) \<longleftrightarrow> (\<forall>t\<in>set ts. invar_otree t \<and> x \<le> root t)"
+text \<open>Heap invariant\<close>
+fun heap :: "'a::linorder tree \<Rightarrow> bool" where
+"heap (Node _ x ts) \<longleftrightarrow> (\<forall>t\<in>set ts. heap t \<and> x \<le> root t)"
 
-definition "invar_tree t \<longleftrightarrow> invar_btree t \<and> invar_otree t"
+definition "bheap t \<longleftrightarrow> btree t \<and> heap t"
 
 text \<open>Binomial Heap invariant\<close>
-definition "invar ts \<longleftrightarrow> (\<forall>t\<in>set ts. invar_tree t) \<and> (sorted_wrt (<) (map rank ts))"
+definition "invar ts \<longleftrightarrow> (\<forall>t\<in>set ts. bheap t) \<and> (sorted_wrt (<) (map rank ts))"
 
 
 text \<open>The children of a node are a valid heap\<close>
 lemma invar_children:
-  "invar_tree (Node r v ts) \<Longrightarrow> invar (rev ts)"
-  by (auto simp: invar_tree_def invar_def rev_map[symmetric])
+  "bheap (Node r v ts) \<Longrightarrow> invar (rev ts)"
+  by (auto simp: bheap_def invar_def rev_map[symmetric])
 
 
 subsection \<open>Operations and Their Functional Correctness\<close>
 
 subsubsection \<open>\<open>link\<close>\<close>
 
 context
 includes pattern_aliases
 begin
 
 fun link :: "('a::linorder) tree \<Rightarrow> 'a tree \<Rightarrow> 'a tree" where
   "link (Node r x\<^sub>1 ts\<^sub>1 =: t\<^sub>1) (Node r' x\<^sub>2 ts\<^sub>2 =: t\<^sub>2) =
     (if x\<^sub>1\<le>x\<^sub>2 then Node (r+1) x\<^sub>1 (t\<^sub>2#ts\<^sub>1) else Node (r+1) x\<^sub>2 (t\<^sub>1#ts\<^sub>2))"
 
 end
 
 lemma invar_link:
-  assumes "invar_tree t\<^sub>1"
-  assumes "invar_tree t\<^sub>2"
+  assumes "bheap t\<^sub>1"
+  assumes "bheap t\<^sub>2"
   assumes "rank t\<^sub>1 = rank t\<^sub>2"
-  shows "invar_tree (link t\<^sub>1 t\<^sub>2)"
-using assms unfolding invar_tree_def
+  shows "bheap (link t\<^sub>1 t\<^sub>2)"
+using assms unfolding bheap_def
 by (cases "(t\<^sub>1, t\<^sub>2)" rule: link.cases) auto
 
 lemma rank_link[simp]: "rank (link t\<^sub>1 t\<^sub>2) = rank t\<^sub>1 + 1"
 by (cases "(t\<^sub>1, t\<^sub>2)" rule: link.cases) simp
 
 lemma mset_link[simp]: "mset_tree (link t\<^sub>1 t\<^sub>2) = mset_tree t\<^sub>1 + mset_tree t\<^sub>2"
 by (cases "(t\<^sub>1, t\<^sub>2)" rule: link.cases) simp
 
 subsubsection \<open>\<open>ins_tree\<close>\<close>
 
-fun ins_tree :: "'a::linorder tree \<Rightarrow> 'a heap \<Rightarrow> 'a heap" where
+fun ins_tree :: "'a::linorder tree \<Rightarrow> 'a trees \<Rightarrow> 'a trees" where
   "ins_tree t [] = [t]"
 | "ins_tree t\<^sub>1 (t\<^sub>2#ts) =
   (if rank t\<^sub>1 < rank t\<^sub>2 then t\<^sub>1#t\<^sub>2#ts else ins_tree (link t\<^sub>1 t\<^sub>2) ts)"
 
-lemma invar_tree0[simp]: "invar_tree (Node 0 x [])"
-unfolding invar_tree_def by auto
+lemma bheap0[simp]: "bheap (Node 0 x [])"
+unfolding bheap_def by auto
 
 lemma invar_Cons[simp]:
   "invar (t#ts)
-  \<longleftrightarrow> invar_tree t \<and> invar ts \<and> (\<forall>t'\<in>set ts. rank t < rank t')"
+  \<longleftrightarrow> bheap t \<and> invar ts \<and> (\<forall>t'\<in>set ts. rank t < rank t')"
 by (auto simp: invar_def)
 
 lemma invar_ins_tree:
-  assumes "invar_tree t"
+  assumes "bheap t"
   assumes "invar ts"
   assumes "\<forall>t'\<in>set ts. rank t \<le> rank t'"
   shows "invar (ins_tree t ts)"
 using assms
 by (induction t ts rule: ins_tree.induct) (auto simp: invar_link less_eq_Suc_le[symmetric])
 
-lemma mset_heap_ins_tree[simp]:
-  "mset_heap (ins_tree t ts) = mset_tree t + mset_heap ts"
+lemma mset_trees_ins_tree[simp]:
+  "mset_trees (ins_tree t ts) = mset_tree t + mset_trees ts"
 by (induction t ts rule: ins_tree.induct) auto
 
 lemma ins_tree_rank_bound:
   assumes "t' \<in> set (ins_tree t ts)"
   assumes "\<forall>t'\<in>set ts. rank t\<^sub>0 < rank t'"
   assumes "rank t\<^sub>0 < rank t"
   shows "rank t\<^sub>0 < rank t'"
 using assms
 by (induction t ts rule: ins_tree.induct) (auto split: if_splits)
 
 subsubsection \<open>\<open>insert\<close>\<close>
 
 hide_const (open) insert
 
-definition insert :: "'a::linorder \<Rightarrow> 'a heap \<Rightarrow> 'a heap" where
+definition insert :: "'a::linorder \<Rightarrow> 'a trees \<Rightarrow> 'a trees" where
 "insert x ts = ins_tree (Node 0 x []) ts"
 
 lemma invar_insert[simp]: "invar t \<Longrightarrow> invar (insert x t)"
 by (auto intro!: invar_ins_tree simp: insert_def)
 
-lemma mset_heap_insert[simp]: "mset_heap (insert x t) = {#x#} + mset_heap t"
+lemma mset_trees_insert[simp]: "mset_trees (insert x t) = {#x#} + mset_trees t"
 by(auto simp: insert_def)
 
 subsubsection \<open>\<open>merge\<close>\<close>
 
 context
 includes pattern_aliases
 begin
 
-fun merge :: "'a::linorder heap \<Rightarrow> 'a heap \<Rightarrow> 'a heap" where
+fun merge :: "'a::linorder trees \<Rightarrow> 'a trees \<Rightarrow> 'a trees" where
   "merge ts\<^sub>1 [] = ts\<^sub>1"
 | "merge [] ts\<^sub>2 = ts\<^sub>2"
 | "merge (t\<^sub>1#ts\<^sub>1 =: h\<^sub>1) (t\<^sub>2#ts\<^sub>2 =: h\<^sub>2) = (
     if rank t\<^sub>1 < rank t\<^sub>2 then t\<^sub>1 # merge ts\<^sub>1 h\<^sub>2 else
     if rank t\<^sub>2 < rank t\<^sub>1 then t\<^sub>2 # merge h\<^sub>1 ts\<^sub>2
     else ins_tree (link t\<^sub>1 t\<^sub>2) (merge ts\<^sub>1 ts\<^sub>2)
   )"
 
 end
 
 lemma merge_simp2[simp]: "merge [] ts\<^sub>2 = ts\<^sub>2"
 by (cases ts\<^sub>2) auto
 
 lemma merge_rank_bound:
   assumes "t' \<in> set (merge ts\<^sub>1 ts\<^sub>2)"
   assumes "\<forall>t\<^sub>1\<in>set ts\<^sub>1. rank t < rank t\<^sub>1"
   assumes "\<forall>t\<^sub>2\<in>set ts\<^sub>2. rank t < rank t\<^sub>2"
   shows "rank t < rank t'"
 using assms
 by (induction ts\<^sub>1 ts\<^sub>2 arbitrary: t' rule: merge.induct)
    (auto split: if_splits simp: ins_tree_rank_bound)
 
 lemma invar_merge[simp]:
   assumes "invar ts\<^sub>1"
   assumes "invar ts\<^sub>2"
   shows "invar (merge ts\<^sub>1 ts\<^sub>2)"
 using assms
 by (induction ts\<^sub>1 ts\<^sub>2 rule: merge.induct)
    (auto 0 3 simp: Suc_le_eq intro!: invar_ins_tree invar_link elim!: merge_rank_bound)
 
 
 text \<open>Longer, more explicit proof of @{thm [source] invar_merge}, 
       to illustrate the application of the @{thm [source] merge_rank_bound} lemma.\<close>
 lemma 
   assumes "invar ts\<^sub>1"
   assumes "invar ts\<^sub>2"
   shows "invar (merge ts\<^sub>1 ts\<^sub>2)"
   using assms
 proof (induction ts\<^sub>1 ts\<^sub>2 rule: merge.induct)
   case (3 t\<^sub>1 ts\<^sub>1 t\<^sub>2 ts\<^sub>2)
   \<comment> \<open>Invariants of the parts can be shown automatically\<close>
   from "3.prems" have [simp]: 
-    "invar_tree t\<^sub>1" "invar_tree t\<^sub>2"
+    "bheap t\<^sub>1" "bheap t\<^sub>2"
     (*"invar (merge (t\<^sub>1#ts\<^sub>1) ts\<^sub>2)" 
     "invar (merge ts\<^sub>1 (t\<^sub>2#ts\<^sub>2))"
     "invar (merge ts\<^sub>1 ts\<^sub>2)"*)
     by auto
 
   \<comment> \<open>These are the three cases of the @{const merge} function\<close>
   consider (LT) "rank t\<^sub>1 < rank t\<^sub>2"
          | (GT) "rank t\<^sub>1 > rank t\<^sub>2"
          | (EQ) "rank t\<^sub>1 = rank t\<^sub>2"
     using antisym_conv3 by blast
   then show ?case proof cases
     case LT 
     \<comment> \<open>@{const merge} takes the first tree from the left heap\<close>
     then have "merge (t\<^sub>1 # ts\<^sub>1) (t\<^sub>2 # ts\<^sub>2) = t\<^sub>1 # merge ts\<^sub>1 (t\<^sub>2 # ts\<^sub>2)" by simp
     also have "invar \<dots>" proof (simp, intro conjI)
       \<comment> \<open>Invariant follows from induction hypothesis\<close>
       show "invar (merge ts\<^sub>1 (t\<^sub>2 # ts\<^sub>2))"
         using LT "3.IH" "3.prems" by simp
 
       \<comment> \<open>It remains to show that \<open>t\<^sub>1\<close> has smallest rank.\<close>
       show "\<forall>t'\<in>set (merge ts\<^sub>1 (t\<^sub>2 # ts\<^sub>2)). rank t\<^sub>1 < rank t'"
         \<comment> \<open>Which is done by auxiliary lemma @{thm [source] merge_rank_bound}\<close>
         using LT "3.prems" by (force elim!: merge_rank_bound)
     qed
     finally show ?thesis .
   next
     \<comment> \<open>@{const merge} takes the first tree from the right heap\<close>
     case GT 
     \<comment> \<open>The proof is anaologous to the \<open>LT\<close> case\<close>
     then show ?thesis using "3.prems" "3.IH" by (force elim!: merge_rank_bound)
   next
     case [simp]: EQ
     \<comment> \<open>@{const merge} links both first trees, and inserts them into the merged remaining heaps\<close>
     have "merge (t\<^sub>1 # ts\<^sub>1) (t\<^sub>2 # ts\<^sub>2) = ins_tree (link t\<^sub>1 t\<^sub>2) (merge ts\<^sub>1 ts\<^sub>2)" by simp
     also have "invar \<dots>" proof (intro invar_ins_tree invar_link) 
       \<comment> \<open>Invariant of merged remaining heaps follows by IH\<close>
       show "invar (merge ts\<^sub>1 ts\<^sub>2)"
         using EQ "3.prems" "3.IH" by auto
 
       \<comment> \<open>For insertion, we have to show that the rank of the linked tree is \<open>\<le>\<close> the 
           ranks in the merged remaining heaps\<close>
       show "\<forall>t'\<in>set (merge ts\<^sub>1 ts\<^sub>2). rank (link t\<^sub>1 t\<^sub>2) \<le> rank t'"
       proof -
         \<comment> \<open>Which is, again, done with the help of @{thm [source] merge_rank_bound}\<close>
         have "rank (link t\<^sub>1 t\<^sub>2) = Suc (rank t\<^sub>2)" by simp
         thus ?thesis using "3.prems" by (auto simp: Suc_le_eq elim!: merge_rank_bound)
       qed
     qed simp_all
     finally show ?thesis .
   qed
 qed auto
 
 
-lemma mset_heap_merge[simp]:
-  "mset_heap (merge ts\<^sub>1 ts\<^sub>2) = mset_heap ts\<^sub>1 + mset_heap ts\<^sub>2"
+lemma mset_trees_merge[simp]:
+  "mset_trees (merge ts\<^sub>1 ts\<^sub>2) = mset_trees ts\<^sub>1 + mset_trees ts\<^sub>2"
 by (induction ts\<^sub>1 ts\<^sub>2 rule: merge.induct) auto
 
 subsubsection \<open>\<open>get_min\<close>\<close>
 
-fun get_min :: "'a::linorder heap \<Rightarrow> 'a" where
+fun get_min :: "'a::linorder trees \<Rightarrow> 'a" where
   "get_min [t] = root t"
 | "get_min (t#ts) = min (root t) (get_min ts)"
 
-lemma invar_tree_root_min:
-  assumes "invar_tree t"
+lemma bheap_root_min:
+  assumes "bheap t"
   assumes "x \<in># mset_tree t"
   shows "root t \<le> x"
-using assms unfolding invar_tree_def
-by (induction t arbitrary: x rule: mset_tree.induct) (fastforce simp: mset_heap_def)
+using assms unfolding bheap_def
+by (induction t arbitrary: x rule: mset_tree.induct) (fastforce simp: mset_trees_def)
 
 lemma get_min_mset:
   assumes "ts\<noteq>[]"
   assumes "invar ts"
-  assumes "x \<in># mset_heap ts"
+  assumes "x \<in># mset_trees ts"
   shows "get_min ts \<le> x"
   using assms
 apply (induction ts arbitrary: x rule: get_min.induct)
 apply (auto
-      simp: invar_tree_root_min min_def intro: order_trans;
-      meson linear order_trans invar_tree_root_min
+      simp: bheap_root_min min_def intro: order_trans;
+      meson linear order_trans bheap_root_min
       )+
 done
 
 lemma get_min_member:
-  "ts\<noteq>[] \<Longrightarrow> get_min ts \<in># mset_heap ts"
+  "ts\<noteq>[] \<Longrightarrow> get_min ts \<in># mset_trees ts"
 by (induction ts rule: get_min.induct) (auto simp: min_def)
 
 lemma get_min:
-  assumes "mset_heap ts \<noteq> {#}"
+  assumes "mset_trees ts \<noteq> {#}"
   assumes "invar ts"
-  shows "get_min ts = Min_mset (mset_heap ts)"
+  shows "get_min ts = Min_mset (mset_trees ts)"
 using assms get_min_member get_min_mset
 by (auto simp: eq_Min_iff)
 
 subsubsection \<open>\<open>get_min_rest\<close>\<close>
 
-fun get_min_rest :: "'a::linorder heap \<Rightarrow> 'a tree \<times> 'a heap" where
+fun get_min_rest :: "'a::linorder trees \<Rightarrow> 'a tree \<times> 'a trees" where
   "get_min_rest [t] = (t,[])"
 | "get_min_rest (t#ts) = (let (t',ts') = get_min_rest ts
                      in if root t \<le> root t' then (t,ts) else (t',t#ts'))"
 
 lemma get_min_rest_get_min_same_root:
   assumes "ts\<noteq>[]"
   assumes "get_min_rest ts = (t',ts')"
   shows "root t' = get_min ts"
 using assms
 by (induction ts arbitrary: t' ts' rule: get_min.induct) (auto simp: min_def split: prod.splits)
 
 lemma mset_get_min_rest:
   assumes "get_min_rest ts = (t',ts')"
   assumes "ts\<noteq>[]"
   shows "mset ts = {#t'#} + mset ts'"
 using assms
 by (induction ts arbitrary: t' ts' rule: get_min.induct) (auto split: prod.splits if_splits)
 
 lemma set_get_min_rest:
   assumes "get_min_rest ts = (t', ts')"
   assumes "ts\<noteq>[]"
   shows "set ts = Set.insert t' (set ts')"
 using mset_get_min_rest[OF assms, THEN arg_cong[where f=set_mset]]
 by auto
 
 lemma invar_get_min_rest:
   assumes "get_min_rest ts = (t',ts')"
   assumes "ts\<noteq>[]"
   assumes "invar ts"
-  shows "invar_tree t'" and "invar ts'"
+  shows "bheap t'" and "invar ts'"
 proof -
-  have "invar_tree t' \<and> invar ts'"
+  have "bheap t' \<and> invar ts'"
     using assms
     proof (induction ts arbitrary: t' ts' rule: get_min.induct)
       case (2 t v va)
       then show ?case
         apply (clarsimp split: prod.splits if_splits)
         apply (drule set_get_min_rest; fastforce)
         done
     qed auto
-  thus "invar_tree t'" and "invar ts'" by auto
+  thus "bheap t'" and "invar ts'" by auto
 qed
 
 subsubsection \<open>\<open>del_min\<close>\<close>
 
-definition del_min :: "'a::linorder heap \<Rightarrow> 'a::linorder heap" where
+definition del_min :: "'a::linorder trees \<Rightarrow> 'a::linorder trees" where
 "del_min ts = (case get_min_rest ts of
    (Node r x ts\<^sub>1, ts\<^sub>2) \<Rightarrow> merge (rev ts\<^sub>1) ts\<^sub>2)"
 
 lemma invar_del_min[simp]:
   assumes "ts \<noteq> []"
   assumes "invar ts"
   shows "invar (del_min ts)"
 using assms
 unfolding del_min_def
 by (auto
       split: prod.split tree.split
       intro!: invar_merge invar_children 
       dest: invar_get_min_rest
     )
 
-lemma mset_heap_del_min:
+lemma mset_trees_del_min:
   assumes "ts \<noteq> []"
-  shows "mset_heap ts = mset_heap (del_min ts) + {# get_min ts #}"
+  shows "mset_trees ts = mset_trees (del_min ts) + {# get_min ts #}"
 using assms
 unfolding del_min_def
 apply (clarsimp split: tree.split prod.split)
 apply (frule (1) get_min_rest_get_min_same_root)
 apply (frule (1) mset_get_min_rest)
-apply (auto simp: mset_heap_def)
+apply (auto simp: mset_trees_def)
 done
 
 
 subsubsection \<open>Instantiating the Priority Queue Locale\<close>
 
 text \<open>Last step of functional correctness proof: combine all the above lemmas
 to show that binomial heaps satisfy the specification of priority queues with merge.\<close>
 
-interpretation binheap: Priority_Queue_Merge
+interpretation bheaps: Priority_Queue_Merge
   where empty = "[]" and is_empty = "(=) []" and insert = insert
   and get_min = get_min and del_min = del_min and merge = merge
-  and invar = invar and mset = mset_heap
+  and invar = invar and mset = mset_trees
 proof (unfold_locales, goal_cases)
   case 1 thus ?case by simp
 next
   case 2 thus ?case by auto
 next
   case 3 thus ?case by auto
 next
   case (4 q)
-  thus ?case using mset_heap_del_min[of q] get_min[OF _ \<open>invar q\<close>]
+  thus ?case using mset_trees_del_min[of q] get_min[OF _ \<open>invar q\<close>]
     by (auto simp: union_single_eq_diff)
 next
   case (5 q) thus ?case using get_min[of q] by auto
 next
   case 6 thus ?case by (auto simp add: invar_def)
 next
   case 7 thus ?case by simp
 next
   case 8 thus ?case by simp
 next
   case 9 thus ?case by simp
 next
   case 10 thus ?case by simp
 qed
 
 
 subsection \<open>Complexity\<close>
 
 text \<open>The size of a binomial tree is determined by its rank\<close>
 lemma size_mset_btree:
-  assumes "invar_btree t"
+  assumes "btree t"
   shows "size (mset_tree t) = 2^rank t"
   using assms
 proof (induction t)
   case (Node r v ts)
   hence IH: "size (mset_tree t) = 2^rank t" if "t \<in> set ts" for t
     using that by auto
 
   from Node have COMPL: "map rank ts = rev [0..<r]" by auto
 
-  have "size (mset_heap ts) = (\<Sum>t\<leftarrow>ts. size (mset_tree t))"
+  have "size (mset_trees ts) = (\<Sum>t\<leftarrow>ts. size (mset_tree t))"
     by (induction ts) auto
   also have "\<dots> = (\<Sum>t\<leftarrow>ts. 2^rank t)" using IH
     by (auto cong: map_cong)
   also have "\<dots> = (\<Sum>r\<leftarrow>map rank ts. 2^r)"
     by (induction ts) auto
   also have "\<dots> = (\<Sum>i\<in>{0..<r}. 2^i)"
     unfolding COMPL
     by (auto simp: rev_map[symmetric] interv_sum_list_conv_sum_set_nat)
   also have "\<dots> = 2^r - 1"
     by (induction r) auto
   finally show ?case
     by (simp)
 qed
 
 lemma size_mset_tree:
-  assumes "invar_tree t"
+  assumes "bheap t"
   shows "size (mset_tree t) = 2^rank t"
-using assms unfolding invar_tree_def
+using assms unfolding bheap_def
 by (simp add: size_mset_btree)
 
 text \<open>The length of a binomial heap is bounded by the number of its elements\<close>
-lemma size_mset_heap:
+lemma size_mset_trees:
   assumes "invar ts"
-  shows "length ts \<le> log 2 (size (mset_heap ts) + 1)"
+  shows "length ts \<le> log 2 (size (mset_trees ts) + 1)"
 proof -
   from \<open>invar ts\<close> have
     ASC: "sorted_wrt (<) (map rank ts)" and
-    TINV: "\<forall>t\<in>set ts. invar_tree t"
+    TINV: "\<forall>t\<in>set ts. bheap t"
     unfolding invar_def by auto
 
   have "(2::nat)^length ts = (\<Sum>i\<in>{0..<length ts}. 2^i) + 1"
     by (simp add: sum_power2)
   also have "\<dots> \<le> (\<Sum>t\<leftarrow>ts. 2^rank t) + 1"
     using sorted_wrt_less_sum_mono_lowerbound[OF _ ASC, of "(^) (2::nat)"]
     using power_increasing[where a="2::nat"]
     by (auto simp: o_def)
   also have "\<dots> = (\<Sum>t\<leftarrow>ts. size (mset_tree t)) + 1" using TINV
     by (auto cong: map_cong simp: size_mset_tree)
-  also have "\<dots> = size (mset_heap ts) + 1"
-    unfolding mset_heap_def by (induction ts) auto
-  finally have "2^length ts \<le> size (mset_heap ts) + 1" .
+  also have "\<dots> = size (mset_trees ts) + 1"
+    unfolding mset_trees_def by (induction ts) auto
+  finally have "2^length ts \<le> size (mset_trees ts) + 1" .
   then show ?thesis using le_log2_of_power by blast
 qed
 
 subsubsection \<open>Timing Functions\<close>
 
 text \<open>
   We define timing functions for each operation, and provide
   estimations of their complexity.
 \<close>
 definition T_link :: "'a::linorder tree \<Rightarrow> 'a tree \<Rightarrow> nat" where
 [simp]: "T_link _ _ = 1"
 
 text \<open>This function is non-canonical: we omitted a \<open>+1\<close> in the \<open>else\<close>-part,
   to keep the following analysis simpler and more to the point.
 \<close>
-fun T_ins_tree :: "'a::linorder tree \<Rightarrow> 'a heap \<Rightarrow> nat" where
+fun T_ins_tree :: "'a::linorder tree \<Rightarrow> 'a trees \<Rightarrow> nat" where
   "T_ins_tree t [] = 1"
 | "T_ins_tree t\<^sub>1 (t\<^sub>2 # ts) = (
     (if rank t\<^sub>1 < rank t\<^sub>2 then 1
      else T_link t\<^sub>1 t\<^sub>2 + T_ins_tree (link t\<^sub>1 t\<^sub>2) ts)
   )"
 
-definition T_insert :: "'a::linorder \<Rightarrow> 'a heap \<Rightarrow> nat" where
+definition T_insert :: "'a::linorder \<Rightarrow> 'a trees \<Rightarrow> nat" where
 "T_insert x ts = T_ins_tree (Node 0 x []) ts + 1"
 
 lemma T_ins_tree_simple_bound: "T_ins_tree t ts \<le> length ts + 1"
 by (induction t ts rule: T_ins_tree.induct) auto
 
 subsubsection \<open>\<open>T_insert\<close>\<close>
 
 lemma T_insert_bound:
   assumes "invar ts"
-  shows "T_insert x ts \<le> log 2 (size (mset_heap ts) + 1) + 2"
+  shows "T_insert x ts \<le> log 2 (size (mset_trees ts) + 1) + 2"
 proof -
   have "real (T_insert x ts) \<le> real (length ts) + 2"
     unfolding T_insert_def using T_ins_tree_simple_bound 
     using of_nat_mono by fastforce
-  also note size_mset_heap[OF \<open>invar ts\<close>]
+  also note size_mset_trees[OF \<open>invar ts\<close>]
   finally show ?thesis by simp
 qed
 
 subsubsection \<open>\<open>T_merge\<close>\<close>
 
 context
 includes pattern_aliases
 begin
 
-fun T_merge :: "'a::linorder heap \<Rightarrow> 'a heap \<Rightarrow> nat" where
+fun T_merge :: "'a::linorder trees \<Rightarrow> 'a trees \<Rightarrow> nat" where
   "T_merge ts\<^sub>1 [] = 1"
 | "T_merge [] ts\<^sub>2 = 1"
 | "T_merge (t\<^sub>1#ts\<^sub>1 =: h\<^sub>1) (t\<^sub>2#ts\<^sub>2 =: h\<^sub>2) = 1 + (
     if rank t\<^sub>1 < rank t\<^sub>2 then T_merge ts\<^sub>1 h\<^sub>2
     else if rank t\<^sub>2 < rank t\<^sub>1 then T_merge h\<^sub>1 ts\<^sub>2
     else T_ins_tree (link t\<^sub>1 t\<^sub>2) (merge ts\<^sub>1 ts\<^sub>2) + T_merge ts\<^sub>1 ts\<^sub>2
   )"
 
 end
 
 text \<open>A crucial idea is to estimate the time in correlation with the
   result length, as each carry reduces the length of the result.\<close>
 
 lemma T_ins_tree_length:
   "T_ins_tree t ts + length (ins_tree t ts) = 2 + length ts"
 by (induction t ts rule: ins_tree.induct) auto
 
 lemma T_merge_length:
-  "length (merge ts\<^sub>1 ts\<^sub>2) + T_merge ts\<^sub>1 ts\<^sub>2 \<le> 2 * (length ts\<^sub>1 + length ts\<^sub>2) + 1"
+  "T_merge ts\<^sub>1 ts\<^sub>2 + length (merge ts\<^sub>1 ts\<^sub>2) \<le> 2 * (length ts\<^sub>1 + length ts\<^sub>2) + 1"
 by (induction ts\<^sub>1 ts\<^sub>2 rule: T_merge.induct)
    (auto simp: T_ins_tree_length algebra_simps)
 
 text \<open>Finally, we get the desired logarithmic bound\<close>
 lemma T_merge_bound:
   fixes ts\<^sub>1 ts\<^sub>2
-  defines "n\<^sub>1 \<equiv> size (mset_heap ts\<^sub>1)"
-  defines "n\<^sub>2 \<equiv> size (mset_heap ts\<^sub>2)"
+  defines "n\<^sub>1 \<equiv> size (mset_trees ts\<^sub>1)"
+  defines "n\<^sub>2 \<equiv> size (mset_trees ts\<^sub>2)"
   assumes "invar ts\<^sub>1" "invar ts\<^sub>2"
   shows "T_merge ts\<^sub>1 ts\<^sub>2 \<le> 4*log 2 (n\<^sub>1 + n\<^sub>2 + 1) + 1"
 proof -
   note n_defs = assms(1,2)
 
   have "T_merge ts\<^sub>1 ts\<^sub>2 \<le> 2 * real (length ts\<^sub>1) + 2 * real (length ts\<^sub>2) + 1"
     using T_merge_length[of ts\<^sub>1 ts\<^sub>2] by simp
-  also note size_mset_heap[OF \<open>invar ts\<^sub>1\<close>]
-  also note size_mset_heap[OF \<open>invar ts\<^sub>2\<close>]
+  also note size_mset_trees[OF \<open>invar ts\<^sub>1\<close>]
+  also note size_mset_trees[OF \<open>invar ts\<^sub>2\<close>]
   finally have "T_merge ts\<^sub>1 ts\<^sub>2 \<le> 2 * log 2 (n\<^sub>1 + 1) + 2 * log 2 (n\<^sub>2 + 1) + 1"
     unfolding n_defs by (simp add: algebra_simps)
   also have "log 2 (n\<^sub>1 + 1) \<le> log 2 (n\<^sub>1 + n\<^sub>2 + 1)" 
     unfolding n_defs by (simp add: algebra_simps)
   also have "log 2 (n\<^sub>2 + 1) \<le> log 2 (n\<^sub>1 + n\<^sub>2 + 1)" 
     unfolding n_defs by (simp add: algebra_simps)
   finally show ?thesis by (simp add: algebra_simps)
 qed
 
 subsubsection \<open>\<open>T_get_min\<close>\<close>
 
-fun T_get_min :: "'a::linorder heap \<Rightarrow> nat" where
+fun T_get_min :: "'a::linorder trees \<Rightarrow> nat" where
   "T_get_min [t] = 1"
 | "T_get_min (t#ts) = 1 + T_get_min ts"
 
 lemma T_get_min_estimate: "ts\<noteq>[] \<Longrightarrow> T_get_min ts = length ts"
 by (induction ts rule: T_get_min.induct) auto
 
 lemma T_get_min_bound:
   assumes "invar ts"
   assumes "ts\<noteq>[]"
-  shows "T_get_min ts \<le> log 2 (size (mset_heap ts) + 1)"
+  shows "T_get_min ts \<le> log 2 (size (mset_trees ts) + 1)"
 proof -
   have 1: "T_get_min ts = length ts" using assms T_get_min_estimate by auto
-  also note size_mset_heap[OF \<open>invar ts\<close>]
+  also note size_mset_trees[OF \<open>invar ts\<close>]
   finally show ?thesis .
 qed
 
 subsubsection \<open>\<open>T_del_min\<close>\<close>
 
-fun T_get_min_rest :: "'a::linorder heap \<Rightarrow> nat" where
+fun T_get_min_rest :: "'a::linorder trees \<Rightarrow> nat" where
   "T_get_min_rest [t] = 1"
 | "T_get_min_rest (t#ts) = 1 + T_get_min_rest ts"
 
 lemma T_get_min_rest_estimate: "ts\<noteq>[] \<Longrightarrow> T_get_min_rest ts = length ts"
   by (induction ts rule: T_get_min_rest.induct) auto
 
 lemma T_get_min_rest_bound:
   assumes "invar ts"
   assumes "ts\<noteq>[]"
-  shows "T_get_min_rest ts \<le> log 2 (size (mset_heap ts) + 1)"
+  shows "T_get_min_rest ts \<le> log 2 (size (mset_trees ts) + 1)"
 proof -
   have 1: "T_get_min_rest ts = length ts" using assms T_get_min_rest_estimate by auto
-  also note size_mset_heap[OF \<open>invar ts\<close>]
+  also note size_mset_trees[OF \<open>invar ts\<close>]
   finally show ?thesis .
 qed
 
 text\<open>Note that although the definition of function \<^const>\<open>rev\<close> has quadratic complexity,
 it can and is implemented (via suitable code lemmas) as a linear time function.
 Thus the following definition is justified:\<close>
 
 definition "T_rev xs = length xs + 1"
 
-definition T_del_min :: "'a::linorder heap \<Rightarrow> nat" where
+definition T_del_min :: "'a::linorder trees \<Rightarrow> nat" where
   "T_del_min ts = T_get_min_rest ts + (case get_min_rest ts of (Node _ x ts\<^sub>1, ts\<^sub>2)
                     \<Rightarrow> T_rev ts\<^sub>1 + T_merge (rev ts\<^sub>1) ts\<^sub>2
   ) + 1"
 
 lemma T_del_min_bound:
   fixes ts
-  defines "n \<equiv> size (mset_heap ts)"
+  defines "n \<equiv> size (mset_trees ts)"
   assumes "invar ts" and "ts\<noteq>[]"
   shows "T_del_min ts \<le> 6 * log 2 (n+1) + 3"
 proof -
   obtain r x ts\<^sub>1 ts\<^sub>2 where GM: "get_min_rest ts = (Node r x ts\<^sub>1, ts\<^sub>2)"
     by (metis surj_pair tree.exhaust_sel)
 
   have I1: "invar (rev ts\<^sub>1)" and I2: "invar ts\<^sub>2"
     using invar_get_min_rest[OF GM \<open>ts\<noteq>[]\<close> \<open>invar ts\<close>] invar_children
     by auto
 
-  define n\<^sub>1 where "n\<^sub>1 = size (mset_heap ts\<^sub>1)"
-  define n\<^sub>2 where "n\<^sub>2 = size (mset_heap ts\<^sub>2)"
+  define n\<^sub>1 where "n\<^sub>1 = size (mset_trees ts\<^sub>1)"
+  define n\<^sub>2 where "n\<^sub>2 = size (mset_trees ts\<^sub>2)"
 
   have "n\<^sub>1 \<le> n" "n\<^sub>1 + n\<^sub>2 \<le> n" unfolding n_def n\<^sub>1_def n\<^sub>2_def
     using mset_get_min_rest[OF GM \<open>ts\<noteq>[]\<close>]
-    by (auto simp: mset_heap_def)
+    by (auto simp: mset_trees_def)
 
   have "T_del_min ts = real (T_get_min_rest ts) + real (T_rev ts\<^sub>1) + real (T_merge (rev ts\<^sub>1) ts\<^sub>2) + 1"
     unfolding T_del_min_def GM
     by simp
   also have "T_get_min_rest ts \<le> log 2 (n+1)" 
     using T_get_min_rest_bound[OF \<open>invar ts\<close> \<open>ts\<noteq>[]\<close>] unfolding n_def by simp
   also have "T_rev ts\<^sub>1 \<le> 1 + log 2 (n\<^sub>1 + 1)"
-    unfolding T_rev_def n\<^sub>1_def using size_mset_heap[OF I1] by simp
+    unfolding T_rev_def n\<^sub>1_def using size_mset_trees[OF I1] by simp
   also have "T_merge (rev ts\<^sub>1) ts\<^sub>2 \<le> 4*log 2 (n\<^sub>1 + n\<^sub>2 + 1) + 1"
     unfolding n\<^sub>1_def n\<^sub>2_def using T_merge_bound[OF I1 I2] by (simp add: algebra_simps)
   finally have "T_del_min ts \<le> log 2 (n+1) + log 2 (n\<^sub>1 + 1) + 4*log 2 (real (n\<^sub>1 + n\<^sub>2) + 1) + 3"
     by (simp add: algebra_simps)
   also note \<open>n\<^sub>1 + n\<^sub>2 \<le> n\<close>
   also note \<open>n\<^sub>1 \<le> n\<close>
   finally show ?thesis by (simp add: algebra_simps)
 qed
 
 end