Theory HOL-Data_Structures.Leftist_Heap
section ‹Leftist Heap›
theory Leftist_Heap
imports
"HOL-Library.Pattern_Aliases"
Tree2
Priority_Queue_Specs
Complex_Main
Define_Time_Function
begin
fun mset_tree :: "('a*'b) tree ⇒ 'a multiset" where
"mset_tree Leaf = {#}" |
"mset_tree (Node l (a, _) r) = {#a#} + mset_tree l + mset_tree r"
type_synonym 'a lheap = "('a*nat)tree"
fun mht :: "'a lheap ⇒ nat" where
"mht Leaf = 0" |
"mht (Node _ (_, n) _) = n"
text‹The invariants:›
fun (in linorder) heap :: "('a*'b) tree ⇒ bool" where
"heap Leaf = True" |
"heap (Node l (m, _) r) =
((∀x ∈ set_tree l ∪ set_tree r. m ≤ x) ∧ heap l ∧ heap r)"
fun ltree :: "'a lheap ⇒ bool" where
"ltree Leaf = True" |
"ltree (Node l (a, n) r) =
(min_height l ≥ min_height r ∧ n = min_height r + 1 ∧ ltree l & ltree r)"
definition empty :: "'a lheap" where
"empty = Leaf"
definition node :: "'a lheap ⇒ 'a ⇒ 'a lheap ⇒ 'a lheap" where
"node l a r =
(let mhl = mht l; mhr = mht r
in if mhl ≥ mhr then Node l (a,mhr+1) r else Node r (a,mhl+1) l)"
fun get_min :: "'a lheap ⇒ 'a" where
"get_min(Node l (a, n) r) = a"
text ‹For function ‹merge›:›
unbundle pattern_aliases
fun merge :: "'a::ord lheap ⇒ 'a lheap ⇒ 'a lheap" where
"merge Leaf t = t" |
"merge t Leaf = t" |
"merge (Node l1 (a1, n1) r1 =: t1) (Node l2 (a2, n2) r2 =: t2) =
(if a1 ≤ a2 then node l1 a1 (merge r1 t2)
else node l2 a2 (merge t1 r2))"
text ‹Termination of @{const merge}: by sum or lexicographic product of the sizes
of the two arguments. Isabelle uses a lexicographic product.›
lemma merge_code: "merge t1 t2 = (case (t1,t2) of
(Leaf, _) ⇒ t2 |
(_, Leaf) ⇒ t1 |
(Node l1 (a1, n1) r1, Node l2 (a2, n2) r2) ⇒
if a1 ≤ a2 then node l1 a1 (merge r1 t2) else node l2 a2 (merge t1 r2))"
by(induction t1 t2 rule: merge.induct) (simp_all split: tree.split)
hide_const (open) insert
definition insert :: "'a::ord ⇒ 'a lheap ⇒ 'a lheap" where
"insert x t = merge (Node Leaf (x,1) Leaf) t"
fun del_min :: "'a::ord lheap ⇒ 'a lheap" where
"del_min Leaf = Leaf" |
"del_min (Node l _ r) = merge l r"
subsection "Lemmas"
lemma mset_tree_empty: "mset_tree t = {#} ⟷ t = Leaf"
by(cases t) auto
lemma mht_eq_min_height: "ltree t ⟹ mht t = min_height t"
by(cases t) auto
lemma ltree_node: "ltree (node l a r) ⟷ ltree l ∧ ltree r"
by(auto simp add: node_def mht_eq_min_height)
lemma heap_node: "heap (node l a r) ⟷
heap l ∧ heap r ∧ (∀x ∈ set_tree l ∪ set_tree r. a ≤ x)"
by(auto simp add: node_def)
lemma set_tree_mset: "set_tree t = set_mset(mset_tree t)"
by(induction t) auto
subsection "Functional Correctness"
lemma mset_merge: "mset_tree (merge t1 t2) = mset_tree t1 + mset_tree t2"
by (induction t1 t2 rule: merge.induct) (auto simp add: node_def ac_simps)
lemma mset_insert: "mset_tree (insert x t) = mset_tree t + {#x#}"
by (auto simp add: insert_def mset_merge)
lemma get_min: "⟦ heap t; t ≠ Leaf ⟧ ⟹ get_min t = Min(set_tree t)"
by (cases t) (auto simp add: eq_Min_iff)
lemma mset_del_min: "mset_tree (del_min t) = mset_tree t - {# get_min t #}"
by (cases t) (auto simp: mset_merge)
lemma ltree_merge: "⟦ ltree l; ltree r ⟧ ⟹ ltree (merge l r)"
by(induction l r rule: merge.induct)(auto simp: ltree_node)
lemma heap_merge: "⟦ heap l; heap r ⟧ ⟹ heap (merge l r)"
proof(induction l r rule: merge.induct)
case 3 thus ?case by(auto simp: heap_node mset_merge ball_Un set_tree_mset)
qed simp_all
lemma ltree_insert: "ltree t ⟹ ltree(insert x t)"
by(simp add: insert_def ltree_merge del: merge.simps split: tree.split)
lemma heap_insert: "heap t ⟹ heap(insert x t)"
by(simp add: insert_def heap_merge del: merge.simps split: tree.split)
lemma ltree_del_min: "ltree t ⟹ ltree(del_min t)"
by(cases t)(auto simp add: ltree_merge simp del: merge.simps)
lemma heap_del_min: "heap t ⟹ heap(del_min t)"
by(cases t)(auto simp add: heap_merge simp del: merge.simps)
text ‹Last step of functional correctness proof: combine all the above lemmas
to show that leftist heaps satisfy the specification of priority queues with merge.›
interpretation lheap: Priority_Queue_Merge
where empty = empty and is_empty = "λt. t = Leaf"
and insert = insert and del_min = del_min
and get_min = get_min and merge = merge
and invar = "λt. heap t ∧ ltree t" and mset = mset_tree
proof(standard, goal_cases)
case 1 show ?case by (simp add: empty_def)
next
case (2 q) show ?case by (cases q) auto
next
case 3 show ?case by(rule mset_insert)
next
case 4 show ?case by(rule mset_del_min)
next
case 5 thus ?case by(simp add: get_min mset_tree_empty set_tree_mset)
next
case 6 thus ?case by(simp add: empty_def)
next
case 7 thus ?case by(simp add: heap_insert ltree_insert)
next
case 8 thus ?case by(simp add: heap_del_min ltree_del_min)
next
case 9 thus ?case by (simp add: mset_merge)
next
case 10 thus ?case by (simp add: heap_merge ltree_merge)
qed
subsection "Complexity"
text ‹Auxiliary time functions (which are both 0):›
time_fun mht
time_fun node
lemma T_mht_0[simp]: "T_mht t = 0"
by(cases t)auto
text ‹Define timing function›
time_fun merge
time_fun insert
time_fun del_min
lemma T_merge_min_height: "ltree l ⟹ ltree r ⟹ T_merge l r ≤ min_height l + min_height r + 1"
proof(induction l r rule: merge.induct)
case 3 thus ?case by(auto)
qed simp_all
corollary T_merge_log: assumes "ltree l" "ltree r"
shows "T_merge l r ≤ log 2 (size1 l) + log 2 (size1 r) + 1"
using le_log2_of_power[OF min_height_size1[of l]]
le_log2_of_power[OF min_height_size1[of r]] T_merge_min_height[of l r] assms
by linarith
corollary T_insert_log: "ltree t ⟹ T_insert x t ≤ log 2 (size1 t) + 2"
using T_merge_log[of "Node Leaf (x, 1) Leaf" t]
by(simp split: tree.split)
lemma ld_ld_1_less:
assumes "x > 0" "y > 0" shows "log 2 x + log 2 y + 1 < 2 * log 2 (x+y)"
proof -
have "2 powr (log 2 x + log 2 y + 1) = 2*x*y"
using assms by(simp add: powr_add)
also have "… < (x+y)^2" using assms
by(simp add: numeral_eq_Suc algebra_simps add_pos_pos)
also have "… = 2 powr (2 * log 2 (x+y))"
using assms by(simp add: powr_add log_powr[symmetric])
finally show ?thesis by simp
qed
corollary T_del_min_log: assumes "ltree t"
shows "T_del_min t ≤ 2 * log 2 (size1 t)"
proof(cases t rule: tree2_cases)
case Leaf thus ?thesis using assms by simp
next
case [simp]: (Node l _ _ r)
have "T_del_min t = T_merge l r" by simp
also have "… ≤ log 2 (size1 l) + log 2 (size1 r) + 1"
using ‹ltree t› T_merge_log[of l r] by (auto simp del: T_merge.simps)
also have "… ≤ 2 * log 2 (size1 t)"
using ld_ld_1_less[of "size1 l" "size1 r"] by (simp)
finally show ?thesis .
qed
end