Sort: Insertion Sort
Recommended Reading
The Insertion-Sort Program
From VFA Require Import Perm.
Fixpoint insert (i:nat) (l: list nat) :=
match l with
| nil => i::nil
| h::t => if i <=? h then i::h::t else h :: insert i t
end.
Fixpoint sort (l: list nat) : list nat :=
match l with
| nil => nil
| h::t => insert h (sort t)
end.
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.
What Sedgewick/Wayne and Cormen/Leiserson/Rivest don't acknowlege
is that the arrays-and-swaps model of sorting is not the only one
in the world. We are writing functional programs, where our
sequences are (typically) represented as linked lists, and where
we do not destructively splice elements into those lists.
Instead, we build new lists that (sometimes) share structure with
the old ones.
So, for example:
The tail of this list, 12::14::18::nil, is not disturbed or
rebuilt by the insert algorithm. The nodes 1::3::4::7::_ are
new, constructed by insert. The first three nodes of the old
list, 1::3::4::_ will likely be garbage-collected, if no other
data structure is still pointing at them. Thus, in this typical
case,
where X and Y are constants, independent of the length of the tail.
The value Y is the number of bytes in one list node: 2 to 4 words,
depending on how the implementation handles constructor-tags.
We write (4-3) to indicate that four list nodes are constructed,
while three list nodes become eligible for garbage collection.
We will not prove such things about the time and space cost, but
they are true anyway, and we should keep them in
consideration.
- Time cost = 4X
- Space cost = (4-3)Y = Y
Specification of Correctness
Inductive sorted: list nat -> Prop :=
| sorted_nil:
sorted nil
| sorted_1: forall x,
sorted (x::nil)
| sorted_cons: forall x y l,
x <= y -> sorted (y::l) -> sorted (x::y::l).
Is this really the right definition of what it means for a list to
be sorted? One might have thought that it should go more like this:
This is a reasonable definition too. It should be equivalent.
Later on, we'll prove that the two definitions really are
equivalent. For now, let's use the first one to define what it
means to be a correct sorting algorthm.
Definition is_a_sorting_algorithm (f: list nat -> list nat) :=
forall al, Permutation al (f al) /\ sorted (f al).
The result (f al) should not only be a sorted sequence,
but it should be some rearrangement (Permutation) of the input sequence.
Proof of Correctness
Exercise: 3 stars (insert_perm)
Prove the following auxiliary lemma, insert_perm, which will be useful for proving sort_perm below. Your proof will be by induction, but you'll need some of the permutation facts from the library, so first remind yourself by doing Search.Search Permutation.
Lemma insert_perm: forall x l, Permutation (x::l) (insert x l).
Proof.
Admitted.
☐
Exercise: 4 stars (insert_sorted)
This one is a bit tricky. However, there just a single induction right at the beginning, and you do not need to use insert_perm or sort_perm.
☐
Now we wrap it all up.
Theorem insertion_sort_correct:
is_a_sorting_algorithm sort.
Proof.
split. apply sort_perm. apply sort_sorted.
Qed.
Making Sure the Specification is Right
Exercise: 4 stars, optional (sorted_sorted')
Hint: Instead of doing induction on the list al, do induction
on the sortedness of al. This proof is a bit tricky, so
you may have to think about how to approach it, and try out
one or two different ideas.
Admitted.
Here, you can't do induction on the sorted'-ness of the list,
because sorted' is not an inductive predicate.
Proof.
Admitted.
☐
Proving Correctness from the Alternate Spec
- insert_perm, sort_perm
- Forall_perm, Permutation_length
- Permutation_sym, Permutation_trans
- a new lemma Forall_nth, stated below.
Exercise: 3 stars, optional (Forall_nth)
Lemma Forall_nth:
forall {A: Type} (P: A -> Prop) d (al: list A),
Forall P al <-> (forall i, i < length al -> P (nth i al d)).
Proof.
Admitted.
forall {A: Type} (P: A -> Prop) d (al: list A),
Forall P al <-> (forall i, i < length al -> P (nth i al d)).
Proof.
Admitted.
☐