# Detailed examples of tactics

This chapter presents detailed examples of certain tactics, to illustrate their behavior.

## dependent induction

The tactics `dependent induction` and `dependent destruction` are another solution for inverting inductive predicate instances and potentially doing induction at the same time. It is based on the `BasicElim` tactic of Conor McBride which works by abstracting each argument of an inductive instance by a variable and constraining it by equalities afterwards. This way, the usual induction and destruct tactics can be applied to the abstracted instance and after simplification of the equalities we get the expected goals.

The abstracting tactic is called generalize_eqs and it takes as argument an hypothesis to generalize. It uses the JMeq datatype defined in Coq.Logic.JMeq, hence we need to require it before. For example, revisiting the first example of the inversion documentation:

Require Import Coq.Logic.JMeq.
Inductive Le : nat -> nat -> Set := | LeO : forall n:nat, Le 0 n | LeS : forall n m:nat, Le n m -> Le (S n) (S m).
  Le is defined Le_rect is defined Le_ind is defined Le_rec is defined
Variable P : nat -> nat -> Prop.
  Toplevel input, characters 0-32: > Variable P : nat -> nat -> Prop. > ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Warning: P is declared as a local axiom [local-declaration,scope] P is declared
Goal forall n m:nat, Le (S n) m -> P n m.
  1 subgoal ============================ forall n m : nat, Le (S n) m -> P n m
intros n m H.
  1 subgoal n, m : nat H : Le (S n) m ============================ P n m

generalize_eqs H.
  1 subgoal n, m, gen_x : nat H : Le gen_x m ============================ gen_x = S n -> P n m

The index `S n` gets abstracted by a variable here, but a corresponding equality is added under the abstract instance so that no information is actually lost. The goal is now almost amenable to do induction or case analysis. One should indeed first move `n` into the goal to strengthen it before doing induction, or `n` will be fixed in the inductive hypotheses (this does not matter for case analysis). As a rule of thumb, all the variables that appear inside constructors in the indices of the hypothesis should be generalized. This is exactly what the `generalize_eqs_vars` variant does:

generalize_eqs_vars H.
induction H.
  2 subgoals n, n0 : nat ============================ 0 = S n -> P n n0 subgoal 2 is: S n0 = S n -> P n (S m)

As the hypothesis itself did not appear in the goal, we did not need to use an heterogeneous equality to relate the new hypothesis to the old one (which just disappeared here). However, the tactic works just as well in this case, e.g.:

Variable Q : forall (n m : nat), Le n m -> Prop.
  Toplevel input, characters 0-48: > Variable Q : forall (n m : nat), Le n m -> Prop. > ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Warning: Q is declared as a local axiom [local-declaration,scope] Q is declared
Goal forall n m (p : Le (S n) m), Q (S n) m p.
  Toplevel input, characters -49–1: Warning: Q is declared as a local axiom [local-declaration,scope] Q is declared 1 subgoal ============================ forall (n m : nat) (p : Le (S n) m), Q (S n) m p

intros n m p.
  1 subgoal n, m : nat p : Le (S n) m ============================ Q (S n) m p
generalize_eqs_vars p.
  1 subgoal m, gen_x : nat p : Le gen_x m ============================ forall (n : nat) (p0 : Le (S n) m), gen_x = S n -> JMeq p p0 -> Q (S n) m p0

One drawback of this approach is that in the branches one will have to substitute the equalities back into the instance to get the right assumptions. Sometimes injection of constructors will also be needed to recover the needed equalities. Also, some subgoals should be directly solved because of inconsistent contexts arising from the constraints on indexes. The nice thing is that we can make a tactic based on discriminate, injection and variants of substitution to automatically do such simplifications (which may involve the K axiom). This is what the `simplify_dep_elim` tactic from `Coq.Program.Equality` does. For example, we might simplify the previous goals considerably:

Require Import Coq.Program.Equality.

induction p ; simplify_dep_elim.
  1 subgoal n, m : nat p : Le n m IHp : forall (n0 : nat) (p0 : Le (S n0) m), n = S n0 -> p ~= p0 -> Q (S n0) m p0 ============================ Q (S n) (S m) (LeS n m p)

The higher-order tactic `do_depind` defined in `Coq.Program.Equality` takes a tactic and combines the building blocks we have seen with it: generalizing by equalities calling the given tactic with the generalized induction hypothesis as argument and cleaning the subgoals with respect to equalities. Its most important instantiations are `dependent induction` and `dependent destruction` that do induction or simply case analysis on the generalized hypothesis. For example we can redo what we’ve done manually with dependent destruction:

Require Import Coq.Program.Equality.

Lemma ex : forall n m:nat, Le (S n) m -> P n m.
  1 subgoal ============================ forall n m : nat, Le (S n) m -> P n m

intros n m H.
  1 subgoal n, m : nat H : Le (S n) m ============================ P n m

dependent destruction H.
  1 subgoal n, m : nat H : Le n m ============================ P n (S m)

This gives essentially the same result as inversion. Now if the destructed hypothesis actually appeared in the goal, the tactic would still be able to invert it, contrary to dependent inversion. Consider the following example on vectors:

Require Import Coq.Program.Equality.

Set Implicit Arguments.

Variable A : Set.
  Toplevel input, characters 0-17: > Variable A : Set. > ^^^^^^^^^^^^^^^^^ Warning: A is declared as a local axiom [local-declaration,scope] A is declared

Inductive vector : nat -> Type := | vnil : vector 0 | vcons : A -> forall n, vector n -> vector (S n).
  vector is defined vector_rect is defined vector_ind is defined vector_rec is defined

Goal forall n, forall v : vector (S n), exists v’ : vector n, exists a : A, v = vcons a v’.
  Toplevel input, characters -139–122: Warning: A is declared as a local axiom [local-declaration,scope] A is declared vector is defined vector_rect is defined vector_ind is defined vector_rec is defined 1 subgoal ============================ forall (n : nat) (v : vector (S n)), exists (v’ : vector n) (a : A), v = vcons a v’

intros n v.
  1 subgoal n : nat v : vector (S n) ============================ exists (v’ : vector n) (a : A), v = vcons a v’

dependent destruction v.
  1 subgoal n : nat a : A v : vector n ============================ exists (v’ : vector n) (a0 : A), vcons a v = vcons a0 v’

In this case, the `v` variable can be replaced in the goal by the generalized hypothesis only when it has a type of the form `vector (S n)`, that is only in the second case of the destruct. The first one is dismissed because `S n <> 0`.

### A larger example

Let’s see how the technique works with induction on inductive predicates on a real example. We will develop an example application to the theory of simply-typed lambda-calculus formalized in a dependently-typed style:

Inductive type : Type := | base : type | arrow : type -> type -> type.
  type is defined type_rect is defined type_ind is defined type_rec is defined

Notation ” t –> t’ ” := (arrow t t’) (at level 20, t’ at next level).

Inductive ctx : Type := | empty : ctx | snoc : ctx -> type -> ctx.
  ctx is defined ctx_rect is defined ctx_ind is defined ctx_rec is defined

Notation ” G , tau ” := (snoc G tau) (at level 20, tau at next level).

Fixpoint conc (G D : ctx) : ctx := match D with | empty => G | snoc D’ x => snoc (conc G D’) x end.
  conc is defined conc is recursively defined (decreasing on 2nd argument)

Notation ” G ; D ” := (conc G D) (at level 20).

Inductive term : ctx -> type -> Type := | ax : forall G tau, term (G, tau) tau | weak : forall G tau, term G tau -> forall tau’, term (G, tau’) tau | abs : forall G tau tau’, term (G , tau) tau’ -> term G (tau –> tau’) | app : forall G tau tau’, term G (tau –> tau’) -> term G tau -> term G tau’.
  term is defined term_rect is defined term_ind is defined term_rec is defined

We have defined types and contexts which are snoc-lists of types. We also have a `conc` operation that concatenates two contexts. The `term` datatype represents in fact the possible typing derivations of the calculus, which are isomorphic to the well-typed terms, hence the name. A term is either an application of:

- the axiom rule to type a reference to the first variable in a context
- the weakening rule to type an object in a larger context
- the abstraction or lambda rule to type a function
- the application to type an application of a function to an argument

Once we have this datatype we want to do proofs on it, like weakening:

Lemma weakening : forall G D tau, term (G ; D) tau -> forall tau’, term (G , tau’ ; D) tau.
  type is defined type_rect is defined type_ind is defined type_rec is defined ctx is defined ctx_rect is defined ctx_ind is defined ctx_rec is defined conc is defined conc is recursively defined (decreasing on 2nd argument) term is defined term_rect is defined term_ind is defined term_rec is defined 1 subgoal ============================ forall (G D : ctx) (tau : type), term (G; D) tau -> forall tau’ : type, term ((G, tau’); D) tau

The problem here is that we can’t just use induction on the typing derivation because it will forget about the `G ; D` constraint appearing in the instance. A solution would be to rewrite the goal as:

Lemma weakening’ : forall G’ tau, term G’ tau -> forall G D, (G ; D) = G’ -> forall tau’, term (G, tau’ ; D) tau.
  1 subgoal ============================ forall (G’ : ctx) (tau : type), term G’ tau -> forall G D : ctx, G; D = G’ -> forall tau’ : type, term ((G, tau’); D) tau

With this proper separation of the index from the instance and the right induction loading (putting `G` and `D` after the inducted-on hypothesis), the proof will go through, but it is a very tedious process. One is also forced to make a wrapper lemma to get back the more natural statement. The `dependent induction` tactic alleviates this trouble by doing all of this plumbing of generalizing and substituting back automatically. Indeed we can simply write:

Require Import Coq.Program.Tactics.

Lemma weakening : forall G D tau, term (G ; D) tau -> forall tau’, term (G , tau’ ; D) tau.
  1 subgoal ============================ forall (G D : ctx) (tau : type), term (G; D) tau -> forall tau’ : type, term ((G, tau’); D) tau

Proof with simpl in * ; simpl_depind ; auto.

intros G D tau H.
  1 subgoal G, D : ctx tau : type H : term (G; D) tau ============================ forall tau’ : type, term ((G, tau’); D) tau
dependent induction H generalizing G D ; intros.
  4 subgoals G0 : ctx tau : type G, D : ctx x : G0, tau = G; D tau’ : type ============================ term ((G, tau’); D) tau subgoal 2 is: term ((G, tau‘0); D) tau subgoal 3 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 4 is: term ((G, tau‘0); D) tau’

This call to dependent induction has an additional arguments which is a list of variables appearing in the instance that should be generalized in the goal, so that they can vary in the induction hypotheses. By default, all variables appearing inside constructors (except in a parameter position) of the instantiated hypothesis will be generalized automatically but one can always give the list explicitly.

Show.
  4 subgoals G0 : ctx tau : type G, D : ctx x : G0, tau = G; D tau’ : type ============================ term ((G, tau’); D) tau subgoal 2 is: term ((G, tau‘0); D) tau subgoal 3 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 4 is: term ((G, tau‘0); D) tau’

The `simpl_depind` tactic includes an automatic tactic that tries to simplify equalities appearing at the beginning of induction hypotheses, generally using trivial applications of `reflexivity`. In cases where the equality is not between constructor forms though, one must help the automation by giving some arguments, using the `specialize` tactic for example.

destruct D… apply weak; apply ax.
  5 subgoals G0 : ctx tau, tau’ : type ============================ term ((G0, tau), tau’) tau subgoal 2 is: term (((G, tau’); D), t) t subgoal 3 is: term ((G, tau‘0); D) tau subgoal 4 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 5 is: term ((G, tau‘0); D) tau’ 4 subgoals G, D : ctx t, tau’ : type ============================ term (((G, tau’); D), t) t subgoal 2 is: term ((G, tau‘0); D) tau subgoal 3 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 4 is: term ((G, tau‘0); D) tau’
apply ax.
  3 subgoals G0 : ctx tau : type H : term G0 tau tau’ : type IHterm : forall G D : ctx, G0 = G; D -> forall tau’ : type, term ((G, tau’); D) tau G, D : ctx x : G0, tau’ = G; D tau‘0 : type ============================ term ((G, tau‘0); D) tau subgoal 2 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 3 is: term ((G, tau‘0); D) tau’

destruct D…
  4 subgoals G0 : ctx tau : type H : term G0 tau tau’ : type IHterm : forall G D : ctx, G0 = G; D -> forall tau’ : type, term ((G, tau’); D) tau tau‘0 : type ============================ term ((G0, tau’), tau‘0) tau subgoal 2 is: term (((G, tau‘0); D), t) tau subgoal 3 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 4 is: term ((G, tau‘0); D) tau’

Show.
  4 subgoals G0 : ctx tau : type H : term G0 tau tau’ : type IHterm : forall G D : ctx, G0 = G; D -> forall tau’ : type, term ((G, tau’); D) tau tau‘0 : type ============================ term ((G0, tau’), tau‘0) tau subgoal 2 is: term (((G, tau‘0); D), t) tau subgoal 3 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 4 is: term ((G, tau‘0); D) tau’

specialize (IHterm G0 empty eq_refl).
  4 subgoals G0 : ctx tau : type H : term G0 tau tau’ : type IHterm : forall tau’ : type, term ((G0, tau’); empty) tau tau‘0 : type ============================ term ((G0, tau’), tau‘0) tau subgoal 2 is: term (((G, tau‘0); D), t) tau subgoal 3 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 4 is: term ((G, tau‘0); D) tau’

Once the induction hypothesis has been narrowed to the right equality, it can be used directly.

apply weak, IHterm.
  3 subgoals tau : type G, D : ctx IHterm : forall G0 D0 : ctx, G; D = G0; D0 -> forall tau’ : type, term ((G0, tau’); D0) tau H : term (G; D) tau t, tau‘0 : type ============================ term (((G, tau‘0); D), t) tau subgoal 2 is: term ((G, tau‘0); D) (tau –> tau’) subgoal 3 is: term ((G, tau‘0); D) tau’

If there is an easy first-order solution to these equations as in this subgoal, the `specialize_eqs` tactic can be used instead of giving explicit proof terms:

specialize_eqs IHterm.
  Toplevel input, characters 0-21: > specialize_eqs IHterm. > ^^^^^^^^^^^^^^^^^^^^^ Error: Ltac call to “specialize_eqs (var)” failed. Specialization not allowed on dependent hypotheses

This concludes our example.

See also: The `induction`, `case`, and `inversion` tactics.

## autorewrite

Here are two examples of `autorewrite` use. The first one ( Ackermann function) shows actually a quite basic use where there is no conditional rewriting. The second one ( Mac Carthy function) involves conditional rewritings and shows how to deal with them using the optional tactic of the `Hint Rewrite` command.

Example 1: Ackermann function

Reset Initial.
  Toplevel input, characters -1851–1834: Warning: A is declared as a local axiom [local-declaration,scope] A is declared vector is defined vector_rect is defined vector_ind is defined vector_rec is defined type is defined type_rect is defined type_ind is defined type_rec is defined ctx is defined ctx_rect is defined ctx_ind is defined ctx_rec is defined conc is defined conc is recursively defined (decreasing on 2nd argument) term is defined term_rect is defined term_ind is defined term_rec is defined type is defined type_rect is defined type_ind is defined type_rec is defined ctx is defined ctx_rect is defined ctx_ind is defined ctx_rec is defined conc is defined conc is recursively defined (decreasing on 2nd argument) term is defined term_rect is defined term_ind is defined term_rec is defined Toplevel input, characters -1851–1834: Warning: A is declared as a local axiom [local-declaration,scope] A is declared vector is defined vector_rect is defined vector_ind is defined vector_rec is defined type is defined type_rect is defined type_ind is defined type_rec is defined ctx is defined ctx_rect is defined ctx_ind is defined ctx_rec is defined conc is defined conc is recursively defined (decreasing on 2nd argument) term is defined term_rect is defined term_ind is defined term_rec is defined

Require Import Arith.
  [Loading ML file z_syntax_plugin.cmxs … done] [Loading ML file quote_plugin.cmxs … done] [Loading ML file newring_plugin.cmxs … done]

Variable Ack : nat -> nat -> nat.
  Toplevel input, characters 0-33: > Variable Ack : nat -> nat -> nat. > ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Warning: Ack is declared as a local axiom [local-declaration,scope] Ack is declared

Axiom Ack0 : forall m:nat, Ack 0 m = S m.
  Ack0 is declared
Axiom Ack1 : forall n:nat, Ack (S n) 0 = Ack n 1.
  Ack1 is declared
Axiom Ack2 : forall n m:nat, Ack (S n) (S m) = Ack n (Ack (S n) m).
  Ack2 is declared

Hint Rewrite Ack0 Ack1 Ack2 : base0.

Lemma ResAck0 : Ack 3 2 = 29.
  1 subgoal ============================ Ack 3 2 = 29

autorewrite with base0 using try reflexivity.
  No more subgoals.

Example 2: Mac Carthy function

Require Import Omega.
  [Loading ML file omega_plugin.cmxs … done]

Variable g : nat -> nat -> nat.
  Toplevel input, characters 0-31: > Variable g : nat -> nat -> nat. > ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Warning: g is declared as a local axiom [local-declaration,scope] g is declared

Axiom g0 : forall m:nat, g 0 m = m.
  g0 is declared
Axiom g1 : forall n m:nat, (n > 0) -> (m > 100) -> g n m = g (pred n) (m - 10).
  g1 is declared
Axiom g2 : forall n m:nat, (n > 0) -> (m <= 100) -> g n m = g (S n) (m + 11).
  g2 is declared

Hint Rewrite g0 g1 g2 using omega : base1.

Lemma Resg0 : g 1 110 = 100.
  Toplevel input, characters -269–238: Warning: g is declared as a local axiom [local-declaration,scope] g is declared g0 is declared g1 is declared g2 is declared 1 subgoal ============================ g 1 110 = 100

Show.
  1 subgoal ============================ g 1 110 = 100

autorewrite with base1 using reflexivity || simpl.
  No more subgoals.

Lemma Resg1 : g 1 95 = 91.
  1 subgoal ============================ g 1 95 = 91

autorewrite with base1 using reflexivity || simpl.
  No more subgoals.

## quote

The tactic `quote` allows using Barendregt’s so-called 2-level approach without writing any ML code. Suppose you have a language `L` of ‘abstract terms’ and a type `A` of ‘concrete terms’ and a function `f : L -> A`. If `L` is a simple inductive datatype and `f` a simple fixpoint, `quote f` will replace the head of current goal by a convertible term of the form `(f t)`. `L` must have a constructor of type: `A -> L`.

Here is an example:

Require Import Quote.

Parameters A B C : Prop.
  A is declared B is declared C is declared

Inductive formula : Type := | f_and : formula -> formula -> formula | f_or : formula -> formula -> formula | f_not : formula -> formula | f_true : formula | f_const : Prop -> formula .
  formula is defined formula_rect is defined formula_ind is defined formula_rec is defined

Fixpoint interp_f (f:formula) : Prop := match f with | f_and f1 f2 => interp_f f1 /\ interp_f f2 | f_or f1 f2 => interp_f f1 \/ interp_f f2 | f_not f1 => ~ interp_f f1 | f_true => True | f_const c => c end.
  interp_f is defined interp_f is recursively defined (decreasing on 1st argument)

Goal A /\ (A \/ True) /\ ~ B /\ (A <-> A).
  A is declared B is declared C is declared formula is defined formula_rect is defined formula_ind is defined formula_rec is defined interp_f is defined interp_f is recursively defined (decreasing on 1st argument) 1 subgoal ============================ A /\ (A \/ True) /\ ~ B /\ (A <-> A)

quote interp_f.
  1 subgoal ============================ interp_f (f_and (f_const A) (f_and (f_or (f_const A) f_true) (f_and (f_not (f_const B)) (f_const (A <-> A)))))

The algorithm to perform this inversion is: try to match the term with right-hand sides expression of `f`. If there is a match, apply the corresponding left-hand side and call yourself recursively on sub- terms. If there is no match, we are at a leaf: return the corresponding constructor (here `f_const`) applied to the term.

Error messages:

1. quote: not a simple fixpoint

   Happens when `quote` is not able to perform inversion properly.

### Introducing variables map

The normal use of quote is to make proofs by reflection: one defines a function `simplify : formula -> formula` and proves a theorem `simplify_ok: (f:formula)(interp_f (simplify f)) -> (interp_f f)`. Then, one can simplify formulas by doing:

quote interp_f.
  1 subgoal ============================ interp_f (f_const (interp_f (f_and (f_const A) (f_and (f_or (f_const A) f_true) (f_and (f_not (f_const B)) (f_const (A <-> A)))))))
apply simplify_ok.
  Toplevel input, characters 6-17: > apply simplify_ok. > ^^^^^^^^^^^ Error: The reference simplify_ok was not found in the current environment.
compute.
  1 subgoal ============================ A /\ (A \/ True) /\ (B -> False) /\ (A -> A) /\ (A -> A)

But there is a problem with leafs: in the example above one cannot write a function that implements, for example, the logical simplifications \(A \wedge A \rightarrow A\) or \(A \wedge \lnot A \rightarrow \mathrm{False}\). This is because `Prop` is impredicative.

It is better to use that type of formulas:

Require Import Quote.

Parameters A B C : Prop.
  A is declared B is declared C is declared

Inductive formula : Set := | f_and : formula -> formula -> formula | f_or : formula -> formula -> formula | f_not : formula -> formula | f_true : formula | f_atom : index -> formula.
  formula is defined formula_rect is defined formula_ind is defined formula_rec is defined

`index` is defined in module `Quote`. Equality on that type is decidable so we are able to simplify \(A \wedge A\) into \(A\) at the abstract level.

When there are variables, there are bindings, and `quote` also provides a type `(varmap A)` of bindings from index to any set `A`, and a function `varmap_find` to search in such maps. The interpretation function also has another argument, a variables map:

Fixpoint interp_f (vm:varmap Prop) (f:formula) {struct f} : Prop := match f with | f_and f1 f2 => interp_f vm f1 /\ interp_f vm f2 | f_or f1 f2 => interp_f vm f1 \/ interp_f vm f2 | f_not f1 => ~ interp_f vm f1 | f_true => True | f_atom i => varmap_find True i vm end.
  interp_f is defined interp_f is recursively defined (decreasing on 2nd argument)

`quote` handles this second case properly:

Goal A /\ (B \/ A) /\ (A \/ ~ B).
  1 subgoal ============================ A /\ (B \/ A) /\ (A \/ ~ B)

quote interp_f.
  1 subgoal ============================ interp_f (Node_vm B (Node_vm A (Empty_vm Prop) (Empty_vm Prop)) (Empty_vm Prop)) (f_and (f_atom (Left_idx End_idx)) (f_and (f_or (f_atom End_idx) (f_atom (Left_idx End_idx))) (f_or (f_atom (Left_idx End_idx)) (f_not (f_atom End_idx)))))

It builds `vm` and `t` such that `(f vm t)` is convertible with the conclusion of current goal.

### Combining variables and constants

One can have both variables and constants in abstracts terms; for example, this is the case for the `ring` tactic. Then one must provide to `quote` a list of constructors of constants. For example, if the list is `[O S]` then closed natural numbers will be considered as constants and other terms as variables.

Example:

Inductive formula : Type := | f_and : formula -> formula -> formula | f_or : formula -> formula -> formula | f_not : formula -> formula | f_true : formula | f_const : Prop -> formula | f_atom : index -> formula.
  Toplevel input, characters 0-297: > Inductive formula : Type := | f_and : formula -> formula -> formula | f_or : formula -> formula -> formula | f_not : formula -> formula | f_true : formula | f_const : Prop -> formula (* constructor for constants *) | f_atom : index -> formula. > ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Error: formula already exists.

Fixpoint interp_f (vm:varmap Prop) (f:formula) {struct f} : Prop := match f with | f_and f1 f2 => interp_f vm f1 /\ interp_f vm f2 | f_or f1 f2 => interp_f vm f1 \/ interp_f vm f2 | f_not f1 => ~ interp_f vm f1 | f_true => True | f_const c => c | f_atom i => varmap_find True i vm end.
  Toplevel input, characters 284-293: > Fixpoint interp_f (vm:varmap Prop) (f:formula) {struct f} : Prop := match f with | f_and f1 f2 => interp_f vm f1 /\ interp_f vm f2 | f_or f1 f2 => interp_f vm f1 \/ interp_f vm f2 | f_not f1 => ~ interp_f vm f1 | f_true => True | f_const c => c | f_atom i => varmap_find True i vm end. > ^^^^^^^^^ Error: Unknown constructor: f_const.

Goal A /\ (A \/ True) /\ ~ B /\ (C <-> C).

quote interp_f [ A B ].
  1 subgoal ============================ interp_f (Node_vm (C <-> C) (Node_vm B (Empty_vm Prop) (Empty_vm Prop)) (Node_vm A (Empty_vm Prop) (Empty_vm Prop))) (f_and (f_atom (Right_idx End_idx)) (f_and (f_or (f_atom (Right_idx End_idx)) f_true) (f_and (f_not (f_atom (Left_idx End_idx))) (f_atom End_idx))))

Undo.
  1 subgoal ============================ A /\ (A \/ True) /\ ~ B /\ (C <-> C)

quote interp_f [ B C iff ].
  1 subgoal ============================ interp_f (Node_vm (C <-> C) (Node_vm B (Empty_vm Prop) (Empty_vm Prop)) (Node_vm A (Empty_vm Prop) (Empty_vm Prop))) (f_and (f_atom (Right_idx End_idx)) (f_and (f_or (f_atom (Right_idx End_idx)) f_true) (f_and (f_not (f_atom (Left_idx End_idx))) (f_atom End_idx))))

Warning: Since function inversion is undecidable in general case, don’t expect miracles from it!

Variant `quote ident in term using tactic`

  `tactic` must be a functional tactic (starting with `fun x =>`) and will be called with the quoted version of term according to `ident`.

Variant `quote ident [ident+] in term using tactic`

  Same as above, but will use the additional `ident` list to chose which subterms are constants (see above).

See also: comments of source file `plugins/quote/quote.ml`

See also: the `ring` tactic.

## Using the tactical language

### About the cardinality of the set of natural numbers

A first example which shows how to use pattern matching over the proof contexts is the proof that natural numbers have more than two elements. The proof of such a lemma can be done as follows:

Lemma card_nat : ~ (exists x : nat, exists y : nat, forall z:nat, x = z \/ y = z).
  1 subgoal ============================ ~ (exists x y : nat, forall z : nat, x = z \/ y = z)
Proof.

red; intros (x, (y, Hy)).
  1 subgoal x, y : nat Hy : forall z : nat, x = z \/ y = z ============================ False

elim (Hy 0); elim (Hy 1); elim (Hy 2); intros; match goal with | [_:(?a = ?b),_:(?a = ?c) |- _ ] => cut (b = c); [ discriminate | transitivity a; auto ] end.
  No more subgoals.

Qed.
  card_nat is defined 1 subgoal ============================ interp_f (Node_vm (C <-> C) (Node_vm B (Empty_vm Prop) (Empty_vm Prop)) (Node_vm A (Empty_vm Prop) (Empty_vm Prop))) (f_and (f_atom (Right_idx End_idx)) (f_and (f_or (f_atom (Right_idx End_idx)) f_true) (f_and (f_not (f_atom (Left_idx End_idx))) (f_atom End_idx))))

We can notice that all the (very similar) cases coming from the three eliminations (with three distinct natural numbers) are successfully solved by a match goal structure and, in particular, with only one pattern (use of non-linear matching).

### Permutation on closed lists

Another more complex example is the problem of permutation on closed lists. The aim is to show that a closed list is a permutation of another one.

First, we define the permutation predicate as shown here:

Section Sort.
  Toplevel input, characters 0-13: > Section Sort. > ^^^^^^^^^^^^^ Error: Proof editing in progress. Proofs currently edited: Unnamed_thm0 Unnamed_thm. Use “Abort All” first or complete proof(s).

Variable A : Set.
  Toplevel input, characters 0-17: > Variable A : Set. > ^^^^^^^^^^^^^^^^^ Warning: A is declared as a local axiom [local-declaration,scope] Toplevel input, characters 0-17: > Variable A : Set. > ^^^^^^^^^^^^^^^^^ Error: A already exists.

Inductive permut : list A -> list A -> Prop := | permut_refl : forall l, permut l l | permut_cons : forall a l0 l1, permut l0 l1 -> permut (a :: l0) (a :: l1) | permut_append : forall a l, permut (a :: l) (l ++ a :: nil) | permut_trans : forall l0 l1 l2, permut l0 l1 -> permut l1 l2 -> permut l0 l2.
  permut is defined permut_ind is defined

End Sort.
  Toplevel input, characters 0-9: > End Sort. > ^^^^^^^^^ Error: Proof editing in progress. Proofs currently edited: Unnamed_thm0 Unnamed_thm. Use “Abort All” first or complete proof(s).

A more complex example is the problem of permutation on closed lists. The aim is to show that a closed list is a permutation of another one. First, we define the permutation predicate as shown above.

Require Import List.

Ltac Permut n := match goal with | |- (permut _ ?l ?l) => apply permut_refl | |- (permut _ (?a :: ?l1) (?a :: ?l2)) => let newn := eval compute in (length l1) in (apply permut_cons; Permut newn) | |- (permut ?A (?a :: ?l1) ?l2) => match eval compute in n with | 1 => fail | _ => let l1’ := constr:(l1 ++ a :: nil) in (apply (permut_trans A (a :: l1) l1’ l2); [ apply permut_append | compute; Permut (pred n) ]) end end.
  Permut is defined

Ltac PermutProve := match goal with | |- (permut _ ?l1 ?l2) => match eval compute in (length l1 = length l2) with | (?n = ?n) => Permut n end end.
  PermutProve is defined

Next, we can write naturally the tactic and the result can be seen above. We can notice that we use two top level definitions `PermutProve` and `Permut`. The function to be called is `PermutProve` which computes the lengths of the two lists and calls `Permut` with the length if the two lists have the same length. `Permut` works as expected. If the two lists are equal, it concludes. Otherwise, if the lists have identical first elements, it applies `Permut` on the tail of the lists. Finally, if the lists have different first elements, it puts the first element of one of the lists (here the second one which appears in the permut predicate) at the end if that is possible, i.e., if the new first element has been at this place previously. To verify that all rotations have been done for a list, we use the length of the list as an argument for Permut and this length is decremented for each rotation down to, but not including, 1 because for a list of length `n`, we can make exactly `n−1` rotations to generate at most `n` distinct lists. Here, it must be noticed that we use the natural numbers of Coq for the rotation counter. In Syntax, we can see that it is possible to use usual natural numbers but they are only used as arguments for primitive tactics and they cannot be handled, in particular, we cannot make computations with them. So, a natural choice is to use Coq data structures so that Coq makes the computations (reductions) by eval compute in and we can get the terms back by match.

With `PermutProve`, we can now prove lemmas as follows:

Lemma permut_ex1 : permut nat (1 :: 2 :: 3 :: nil) (3 :: 2 :: 1 :: nil).
  permut is defined permut_ind is defined Permut is defined PermutProve is defined Toplevel input, characters 26-29: > Lemma permut_ex1 : permut nat (1 :: 2 :: 3 :: nil) (3 :: 2 :: 1 :: nil). > ^^^ Error: The term “nat” has type “Set” while it is expected to have type “list A“.

Proof.
PermutProve.
  Toplevel input, characters 0-12: > PermutProve. > ^^^^^^^^^^^^ Error: No matching clauses for match.
Qed.
  permut is defined permut_ind is defined Permut is defined PermutProve is defined Toplevel input, characters 0-4: > Qed. > ^^^^ Error: Attempt to save an incomplete proof (in proof Unnamed_thm0)

Lemma permut_ex2 : permut nat (0 :: 1 :: 2 :: 3 :: 4 :: 5 :: 6 :: 7 :: 8 :: 9 :: nil) (0 :: 2 :: 4 :: 6 :: 8 :: 9 :: 7 :: 5 :: 3 :: 1 :: nil).
  Toplevel input, characters 26-29: > Lemma permut_ex2 : permut nat (0 :: 1 :: 2 :: 3 :: 4 :: 5 :: 6 :: 7 :: 8 :: 9 :: nil) (0 :: 2 :: 4 :: 6 :: 8 :: 9 :: 7 :: 5 :: 3 :: 1 :: nil). > ^^^ Error: The term “nat” has type “Set” while it is expected to have type “list A“.
Proof.
PermutProve.
  Toplevel input, characters 0-12: > PermutProve. > ^^^^^^^^^^^^ Error: No matching clauses for match.
Qed.
  Toplevel input, characters 0-4: > Qed. > ^^^^ Error: Attempt to save an incomplete proof (in proof Unnamed_thm0)

### Deciding intuitionistic propositional logic

Ltac Axioms := match goal with | |- True => trivial | _:False |- _ => elimtype False; assumption | _:?A |- ?A => auto end.
  Axioms is defined

Ltac DSimplif := repeat (intros; match goal with | id:(~ _) |- _ => red in id | id:(_ /\ _) |- _ => elim id; do 2 intro; clear id | id:(_ \/ _) |- _ => elim id; intro; clear id | id:(?A /\ ?B -> ?C) |- _ => cut (A -> B -> C); [ intro | intros; apply id; split; assumption ] | id:(?A \/ ?B -> ?C) |- _ => cut (B -> C); [ cut (A -> C); [ intros; clear id | intro; apply id; left; assumption ] | intro; apply id; right; assumption ] | id0:(?A -> ?B),id1:?A |- _ => cut B; [ intro; clear id0 | apply id0; assumption ] | |- (_ /\ _) => split | |- (~ _) => red end).
  DSimplif is defined

Ltac TautoProp := DSimplif; Axioms || match goal with | id:((?A -> ?B) -> ?C) |- _ => cut (B -> C); [ intro; cut (A -> B); [ intro; cut C; [ intro; clear id | apply id; assumption ] | clear id ] | intro; apply id; intro; assumption ]; TautoProp | id:(~ ?A -> ?B) |- _ => cut (False -> B); [ intro; cut (A -> False); [ intro; cut B; [ intro; clear id | apply id; assumption ] | clear id ] | intro; apply id; red; intro; assumption ]; TautoProp | |- (_ \/ _) => (left; TautoProp) || (right; TautoProp) end.
  TautoProp is defined

The pattern matching on goals allows a complete and so a powerful backtracking when returning tactic values. An interesting application is the problem of deciding intuitionistic propositional logic. Considering the contraction-free sequent calculi LJT* of Roy Dyckhoff [Dyc92], it is quite natural to code such a tactic using the tactic language as shown on figures: Deciding intuitionistic propositions (1) and Deciding intuitionistic propositions (2). The tactic `Axioms` tries to conclude using usual axioms. The tactic `DSimplif` applies all the reversible rules of Dyckhoff’s system. Finally, the tactic `TautoProp` (the main tactic to be called) simplifies with `DSimplif`, tries to conclude with `Axioms` and tries several paths using the backtracking rules (one of the four Dyckhoff’s rules for the left implication to get rid of the contraction and the right or).

For example, with `TautoProp`, we can prove tautologies like those:

Lemma tauto_ex1 : forall A B:Prop, A /\ B -> A \/ B.
  Axioms is defined DSimplif is defined TautoProp is defined 1 subgoal ============================ forall A0 B0 : Prop, A0 /\ B0 -> A0 \/ B0

Proof.
TautoProp.
  No more subgoals.
Qed.
  tauto_ex1 is defined 1 subgoal ============================ interp_f (Node_vm (C <-> C) (Node_vm B (Empty_vm Prop) (Empty_vm Prop)) (Node_vm A (Empty_vm Prop) (Empty_vm Prop))) (f_and (f_atom (Right_idx End_idx)) (f_and (f_or (f_atom (Right_idx End_idx)) f_true) (f_and (f_not (f_atom (Left_idx End_idx))) (f_atom End_idx))))

Lemma tauto_ex2 : forall A B:Prop, (~ ~ B -> B) -> (A -> B) -> ~ ~ A -> B.
  1 subgoal ============================ forall A0 B0 : Prop, (~ ~ B0 -> B0) -> (A0 -> B0) -> ~ ~ A0 -> B0

Proof.
TautoProp.
  No more subgoals.
Qed.
  tauto_ex2 is defined 1 subgoal ============================ interp_f (Node_vm (C <-> C) (Node_vm B (Empty_vm Prop) (Empty_vm Prop)) (Node_vm A (Empty_vm Prop) (Empty_vm Prop))) (f_and (f_atom (Right_idx End_idx)) (f_and (f_or (f_atom (Right_idx End_idx)) f_true) (f_and (f_not (f_atom (Left_idx End_idx))) (f_atom End_idx))))

### Deciding type isomorphisms

A more tricky problem is to decide equalities between types and modulo isomorphisms. Here, we choose to use the isomorphisms of the simply typed λ-calculus with Cartesian product and unit type (see, for example, [dC95]). The axioms of this λ-calculus are given below.

Open Scope type_scope.

Section Iso_axioms.

Variables A B C : Set.
  A is declared B is declared C is declared

Axiom Com : A * B = B * A.
  Com is declared
Axiom Ass : A * (B * C) = A * B * C.
  Ass is declared
Axiom Cur : (A * B -> C) = (A -> B -> C).
  Cur is declared
Axiom Dis : (A -> B * C) = (A -> B) * (A -> C).
  Dis is declared
Axiom P_unit : A * unit = A.
  P_unit is declared
Axiom AR_unit : (A -> unit) = unit.
  AR_unit is declared
Axiom AL_unit : (unit -> A) = A.
  AL_unit is declared

Lemma Cons : B = C -> A * B = A * C.
  1 subgoal A, B, C : Set ============================ B = C -> A * B = A * C
Proof.
intro Heq; rewrite Heq; reflexivity.
  No more subgoals.
Qed.
  Cons is defined

End Iso_axioms.

Ltac DSimplif trm := match trm with | (?A * ?B * ?C) => rewrite <- (Ass A B C); try MainSimplif | (?A * ?B -> ?C) => rewrite (Cur A B C); try MainSimplif | (?A -> ?B * ?C) => rewrite (Dis A B C); try MainSimplif | (?A * unit) => rewrite (P_unit A); try MainSimplif | (unit * ?B) => rewrite (Com unit B); try MainSimplif | (?A -> unit) => rewrite (AR_unit A); try MainSimplif | (unit -> ?B) => rewrite (AL_unit B); try MainSimplif | (?A * ?B) => (DSimplif A; try MainSimplif) || (DSimplif B; try MainSimplif) | (?A -> ?B) => (DSimplif A; try MainSimplif) || (DSimplif B; try MainSimplif) end with MainSimplif := match goal with | |- (?A = ?B) => try DSimplif A; try DSimplif B end.
  DSimplif is defined MainSimplif is defined

Ltac Length trm := match trm with | (_ * ?B) => let succ := Length B in constr:(S succ) | _ => constr:(1) end.
  Length is defined

Ltac assoc := repeat rewrite <- Ass.
  assoc is defined

Ltac DoCompare n := match goal with | [ |- (?A = ?A) ] => reflexivity | [ |- (?A * ?B = ?A * ?C) ] => apply Cons; let newn := Length B in DoCompare newn | [ |- (?A * ?B = ?C) ] => match eval compute in n with | 1 => fail | _ => pattern (A * B) at 1; rewrite Com; assoc; DoCompare (pred n) end end.
  DoCompare is defined

Ltac CompareStruct := match goal with | [ |- (?A = ?B) ] => let l1 := Length A with l2 := Length B in match eval compute in (l1 = l2) with | (?n = ?n) => DoCompare n end end.
  CompareStruct is defined

Ltac IsoProve := MainSimplif; CompareStruct.
  IsoProve is defined

The tactic to judge equalities modulo this axiomatization can be written as shown on these figures: type isomorphism tactic (1) and type isomorphism tactic (2). The algorithm is quite simple. Types are reduced using axioms that can be oriented (this done by `MainSimplif`). The normal forms are sequences of Cartesian products without Cartesian product in the left component. These normal forms are then compared modulo permutation of the components (this is done by `CompareStruct`). The main tactic to be called and realizing this algorithm isIsoProve.

Here are examples of what can be solved by `IsoProve`.

Lemma isos_ex1 : forall A B:Set, A * unit * B = B * (unit * A).
  1 subgoal ============================ forall A B : Set, A * unit * B = B * (unit * A)
Proof.
intros; IsoProve.
  No more subgoals.
Qed.
  isos_ex1 is defined

Lemma isos_ex2 : forall A B C:Set, (A * unit -> B * (C * unit)) = (A * unit -> (C -> unit) * C) * (unit -> A -> B).
  1 subgoal ============================ forall A B C : Set, (A * unit -> B * (C * unit)) = (A * unit -> (C -> unit) * C) * (unit -> A -> B)
Proof.
intros; IsoProve.
  No more subgoals.
Qed.
  isos_ex2 is defined