# MultisetInsertion Sort With Multisets

We have seen how to specify algorithms on "collections", such as sorting algorithms, using permutations. Instead of using permutations, another way to specify these algorithms is to use multisets. A set of values is like a list with no repeats where the order does not matter. A multiset is like a list, possibly with repeats, where the order does not matter. One simple representation of a multiset is a function from values to nat.
From Coq Require Import Strings.String.
From VFA Require Import Perm.
From VFA Require Import Sort.
Require Export FunctionalExtensionality.
In this chapter we will be using natural numbers for two different purposes: the values in the lists that we sort, and the multiplicity (number of times occurring) of those values. To keep things straight, we'll use the value type for values, and nat for multiplicities.
Definition value := nat.

Definition multiset := valuenat.
Just like sets, multisets have operators for union, for the empty multiset, and the multiset with just a single element.
Definition empty : multiset :=
fun x ⇒ 0.

Definition union (a b : multiset) : multiset :=
fun xa x + b x.

Definition singleton (v: value) : multiset :=
fun xif x =? v then 1 else 0.

#### Exercise: 1 star, standard (union_assoc)

Since multisets are represented as functions, to prove that one multiset equals another we must use the axiom of functional extensionality.
Lemma union_assoc: a b c : multiset, (* assoc stands for "associative" *)
union a (union b c) = union (union a b) c.
Proof.
intros.
extensionality x.
(* FILL IN HERE *) Admitted.

#### Exercise: 1 star, standard (union_comm)

Lemma union_comm: a b : multiset, (* comm stands for "commutative" *)
union a b = union b a.
Proof.
(* FILL IN HERE *) Admitted.
Remark on efficiency: These multisets aren't very efficient. If you wrote programs with them, the programs would run slowly. However, we're using them for specifications, not for programs. Our multisets built with union and singleton will never really execute on any large-scale inputs; they're only used in the proof of correctness of algorithms such as sort. Therefore, their inefficiency is not a problem.
Contents of a list, as a multiset:
Fixpoint contents (al: list value) : multiset :=
match al with
| a :: blunion (singleton a) (contents bl)
| nilempty
end.
Recall the insertion-sort program from Sort.v. Note that it handles lists with repeated elements just fine.
Example sort_pi: sort [3;1;4;1;5;9;2;6;5;3;5] = [1;1;2;3;3;4;5;5;5;6;9].
Proof. simpl. reflexivity. Qed.

Example sort_pi_same_contents:
contents (sort [3;1;4;1;5;9;2;6;5;3;5]) = contents [3;1;4;1;5;9;2;6;5;3;5].
Proof.
extensionality x.
repeat (destruct x; try reflexivity).
(* Why does this work? Try it step by step, without repeat *)
Qed.

# Correctness

A sorting algorithm must rearrange the elements into a list that is totally ordered. But let's say that a different way: the algorithm must produce a list with the same multiset of values, and this list must be totally ordered.
Definition is_a_sorting_algorithm' (f: list natlist nat) :=
al, contents al = contents (f al) ∧ sorted (f al).

#### Exercise: 3 stars, standard (insert_contents)

First, prove the auxiliary lemma insert_contents, which will be useful for proving sort_contents below. Your proof will be by induction. You do not need to use extensionality, but do make use of the lemmas about union you proved above.
Lemma insert_contents: x l, contents (x::l) = contents (insert x l).
Proof.
(* FILL IN HERE *) Admitted.

#### Exercise: 3 stars, standard (sort_contents)

Now prove that sort preserves contents.
Theorem sort_contents: l, contents l = contents (sort l).
(* FILL IN HERE *) Admitted.
Now we wrap it all up.
Theorem insertion_sort_correct:
is_a_sorting_algorithm' sort.
Proof.
split. apply sort_contents. apply sort_sorted.
Qed.

#### Exercise: 1 star, standard, optional (permutations_vs_multiset)

Compare your proofs of insert_perm, sort_perm with your proofs of insert_contents, sort_contents. Which proofs are simpler?
• easier with permutations,
• easier with multisets
Regardless of "difficulty", which do you prefer / find easier to think about?
• permutations or
• multisets
Put an X in one box in each list.
(* Do not modify the following line: *)
Definition manual_grade_for_permutations_vs_multiset : option (nat*string) := None.

# Permutations and Multisets

The two specifications of insertion sort are equivalent. One reason is that permutations and multisets are closely related. We're going to prove:
Permutation al bl contents al = contents bl.

#### Exercise: 3 stars, standard (perm_contents)

The forward direction is easy, by induction on the evidence for Permutation:
Lemma perm_contents:
al bl : list nat,
Permutation al blcontents al = contents bl.
(* FILL IN HERE *) Admitted.
The other direction, contents al = contents bl Permutation al bl, is surprisingly difficult. (Or maybe there's an easy way that I didn't find.)
Fixpoint list_delete (al: list value) (v: value) :=
match al with
| x::blif x =? v then bl else x :: list_delete bl v
| nilnil
end.

Definition multiset_delete (m: multiset) (v: value) :=
fun xif x =? v then pred(m x) else m x.

#### Exercise: 3 stars, standard (delete_contents)

Lemma delete_contents:
v al,
contents (list_delete al v) = multiset_delete (contents al) v.
Proof.
intros.
extensionality x.
induction al.
simpl. unfold empty, multiset_delete.
bdestruct (x =? v); auto.
simpl.
bdestruct (a =? v).
(* FILL IN HERE *) Admitted.

#### Exercise: 2 stars, standard (contents_perm_aux)

Lemma contents_perm_aux:
v b, empty = union (singleton v) bFalse.
Proof.
(* FILL IN HERE *) Admitted.

#### Exercise: 2 stars, standard (contents_in)

Lemma contents_in:
(a: value) (bl: list value) , contents bl a > 0 → In a bl.
Proof.
(* FILL IN HERE *) Admitted.

#### Exercise: 2 stars, standard (in_perm_delete)

Lemma in_perm_delete:
a bl,
In a blPermutation (a :: list_delete bl a) bl.
Proof.
(* FILL IN HERE *) Admitted.

#### Exercise: 4 stars, standard (contents_perm)

Lemma contents_perm:
al bl, contents al = contents blPermutation al bl.
Proof.
induction al; destruct bl; intro.
auto.
simpl in H.
simpl in H. symmetry in H.
specialize (IHal (list_delete (v :: bl) a)).
remember (v::bl) as cl.
clear v bl Heqcl.
From this point on, you don't need induction. Use the lemmas perm_trans, delete_contents, in_perm_delete, contents_in. At certain points you'll need to unfold the definitions of multiset_delete, union, singleton.
(* FILL IN HERE *) Admitted.

# The Main Theorem: Equivalence of Multisets and Permutations

Theorem same_contents_iff_perm:
al bl, contents al = contents blPermutation al bl.
Proof.
intros. split. apply contents_perm. apply perm_contents.
Qed.
Therefore, it doesn't matter whether you prove your sorting algorithm using the Permutations method or the multiset method.
Corollary sort_specifications_equivalent:
sort, is_a_sorting_algorithm sortis_a_sorting_algorithm' sort.
Proof.
unfold is_a_sorting_algorithm, is_a_sorting_algorithm'.
split; intros;
destruct (H al); split; auto;
apply same_contents_iff_perm; auto.
Qed.

(* Thu May 2 14:47:51 EDT 2019 *)