MapsTotal and Partial Maps

Maps (or dictionaries) are ubiquitous data structures, both in software construction generally and in the theory of programming languages in particular; we're going to need them in many places in the coming chapters. They also make a nice case study using ideas we've seen in previous chapters, including building data structures out of higher-order functions (from Basics and Poly) and the use of reflection to streamline proofs (from IndProp).
We'll define two flavors of maps: total maps, which include a "default" element to be returned when a key being looked up doesn't exist, and partial maps, which return an option to indicate success or failure. The latter is defined in terms of the former, using None as the default element.

The Coq Standard Library

One small digression before we start.
Unlike the chapters we have seen so far, this one does not Require Import the chapter before it (and, transitively, all the earlier chapters). Instead, in this chapter and from now, on we're going to import the definitions and theorems we need directly from Coq's standard library stuff. You should not notice much difference, though, because we've been careful to name our own definitions and theorems the same as their counterparts in the standard library, wherever they overlap.

Require Import Coq.Arith.Arith.
Require Import Coq.Bool.Bool.
Require Import Coq.Logic.FunctionalExtensionality.

Documentation for the standard library can be found at http://coq.inria.fr/library/.
The SearchAbout command is a good way to look for theorems involving objects of specific types.

Identifiers

First, we need a type for the keys that we use to index into our maps. For this purpose, we again use the type id from the Lists chapter. To make this chapter self contained, we repeat its definition here, together with the equality comparison function for ids and its fundamental property.

Inductive id : Type :=
  | Id : nat id.

Definition beq_id x y :=
  match x,y with
    | Id n1, Id n2beq_nat n1 n2
  end.

Theorem beq_id_refl : id, true = beq_id id id.
Proof.
  intros [n]. simpl. rewrite beq_nat_refl.
  reflexivity. Qed.

The following useful property of beq_id follows from an analogous lemma about numbers:

Theorem beq_id_true_iff : x y : id,
  beq_id x y = true x = y.
Proof.
   intros [n1] [n2].
   unfold beq_id.
   rewrite beq_nat_true_iff.
   split.
   - (* -> *) intros H. rewrite H. reflexivity.
   - (* <- *) intros H. inversion H. reflexivity.
Qed.

Similarly:

Theorem beq_id_false_iff : x y : id,
  beq_id x y = false
   xy.
Proof.
  intros x y. rewrite beq_id_true_iff.
  rewrite not_true_iff_false. reflexivity. Qed.

This useful variant follows just by rewriting:

Theorem false_beq_id : x y : id,
   xy
    beq_id x y = false.
Proof.
  intros x y. rewrite beq_id_false_iff.
  intros H. apply H. Qed.

Total Maps

Our main job in this chapter will be to build a definition of partial maps that is similar in behavior to the one we saw in the Lists chapter, plus accompanying lemmas about their behavior.
This time around, though, we're going to use functions, rather than lists of key-value pairs, to build maps. The advantage of this representation is that it offers a more extensional view of maps, where two maps that respond to queries in the same way will be represented as literally the same thing (the same function), rather than just "equivalent" data structures. This, in turn, simplifies proofs that use maps.
We build partial maps in two steps. First, we define a type of total maps that return a default value when we look up a key that is not present in the map.

Definition total_map (A:Type) := id A.

Intuitively, a total map over an element type A is just a function that can be used to look up ids, yielding As.
The function t_empty yields an empty total map, given a default element; this map always returns the default element when applied to any id.

Definition t_empty {A:Type} (v : A) : total_map A :=
  (fun _v).

More interesting is the update function, which (as before) takes a map m, a key x, and a value v and returns a new map that takes x to v and takes every other key to whatever m does.

Definition t_update {A:Type} (m : total_map A)
                    (x : id) (v : A) :=
  fun x'if beq_id x x' then v else m x'.

This definition is a nice example of higher-order programming. The t_update function takes a function m and yields a new function fun x' ... that behaves like the desired map.
For example, we can build a map taking ids to bools, where Id 3 is mapped to true and every other key is mapped to false, like this:

Definition examplemap :=
  t_update (t_update (t_empty false) (Id 1) false)
           (Id 3) true.

This completes the definition of total maps. Note that we don't need to define a find operation because it is just function application!

Example update_example1 : examplemap (Id 0) = false.
Proof. reflexivity. Qed.

Example update_example2 : examplemap (Id 1) = false.
Proof. reflexivity. Qed.

Example update_example3 : examplemap (Id 2) = false.
Proof. reflexivity. Qed.

Example update_example4 : examplemap (Id 3) = true.
Proof. reflexivity. Qed.

To use maps in later chapters, we'll need several fundamental facts about how they behave. Even if you don't work the following exercises, make sure you thoroughly understand the statements of the lemmas! (Some of the proofs require the functional extensionality axiom, which is discussed in the Logic chapter and included in the Coq standard library.)

Exercise: 1 star, optional (t_apply_empty)

First, the empty map returns its default element for all keys:
Lemma t_apply_empty: A x v, @t_empty A v x = v.
Proof.
  (* FILL IN HERE *) Admitted.

Exercise: 2 stars, optional (t_update_eq)

Next, if we update a map m at a key x with a new value v and then look up x in the map resulting from the update, we get back v:

Lemma t_update_eq : A (m: total_map A) x v,
  (t_update m x v) x = v.
Proof.
  (* FILL IN HERE *) Admitted.

Exercise: 2 stars, optional (t_update_neq)

On the other hand, if we update a map m at a key x1 and then look up a different key x2 in the resulting map, we get the same result that m would have given:

Theorem t_update_neq : (X:Type) v x1 x2
                         (m : total_map X),
  x1x2
  (t_update m x1 v) x2 = m x2.
Proof.
  (* FILL IN HERE *) Admitted.

Exercise: 2 stars, optional (t_update_shadow)

If we update a map m at a key x with a value v1 and then update again with the same key x and another value v2, the resulting map behaves the same (gives the same result when applied to any key) as the simpler map obtained by performing just the second update on m:

Lemma t_update_shadow : A (m: total_map A) v1 v2 x,
    t_update (t_update m x v1) x v2
  = t_update m x v2.
Proof.
  (* FILL IN HERE *) Admitted.
For the final two lemmas about total maps, it's convenient to use the reflection idioms introduced in chapter IndProp. We begin by proving a fundamental reflection lemma relating the equality proposition on ids with the boolean function beq_id.

Exercise: 2 stars (beq_idP)

Use the proof of beq_natP in chapter IndProp as a template to prove the following:

Lemma beq_idP : x y, reflect (x = y) (beq_id x y).
Proof.
  (* FILL IN HERE *) Admitted.
Now, given ids x1 and x2, we can use the destruct (beq_idP x1 x2) to simultaneously perform case analysis on the result of beq_id x1 x2 and generate hypotheses about the equality (in the sense of =) of x1 and x2.

Exercise: 2 stars (t_update_same)

Using the example in chapter IndProp as a template, use beq_idP to prove the following theorem, which states that if we update a map to assign key x the same value as it already has in m, then the result is equal to m:

Theorem t_update_same : X x (m : total_map X),
  t_update m x (m x) = m.
Proof.
  (* FILL IN HERE *) Admitted.

Exercise: 3 stars, recommended (t_update_permute)

Use beq_idP to prove one final property of the update function: If we update a map m at two distinct keys, it doesn't matter in which order we do the updates.

Theorem t_update_permute : (X:Type) v1 v2 x1 x2
                             (m : total_map X),
  x2x1
    (t_update (t_update m x2 v2) x1 v1)
  = (t_update (t_update m x1 v1) x2 v2).
Proof.
  (* FILL IN HERE *) Admitted.

Partial maps

Finally, we define partial maps on top of total maps. A partial map with elements of type A is simply a total map with elements of type option A and default element None.

Definition partial_map (A:Type) := total_map (option A).

Definition empty {A:Type} : partial_map A :=
  t_empty None.

Definition update {A:Type} (m : partial_map A)
                  (x : id) (v : A) :=
  t_update m x (Some v).

We can now lift all of the basic lemmas about total maps to partial maps.

Lemma apply_empty : A x, @empty A x = None.
Proof.
  intros. unfold empty. rewrite t_apply_empty.
  reflexivity.
Qed.

Lemma update_eq : A (m: partial_map A) x v,
  (update m x v) x = Some v.
Proof.
  intros. unfold update. rewrite t_update_eq.
  reflexivity.
Qed.

Theorem update_neq : (X:Type) v x1 x2
                       (m : partial_map X),
  x2x1
  (update m x2 v) x1 = m x1.
Proof.
  intros X v x1 x2 m H.
  unfold update. rewrite t_update_neq. reflexivity.
  apply H. Qed.

Lemma update_shadow : A (m: partial_map A) v1 v2 x,
  update (update m x v1) x v2 = update m x v2.
Proof.
  intros A m v1 v2 x1. unfold update. rewrite t_update_shadow.
  reflexivity.
Qed.

Theorem update_same : X v x (m : partial_map X),
  m x = Some v
  update m x v = m.
Proof.
  intros X v x m H. unfold update. rewrite H.
  apply t_update_same.
Qed.

Theorem update_permute : (X:Type) v1 v2 x1 x2
                                (m : partial_map X),
  x2x1
    (update (update m x2 v2) x1 v1)
  = (update (update m x1 v1) x2 v2).
Proof.
  intros X v1 v2 x1 x2 m. unfold update.
  apply t_update_permute.
Qed.