deduce

Writing Proofs in Deduce

This section provides a tutorial on writing proofs in Deduce. In the following subsections we introduce the features of the Deduce proof language and provide examples of their use.

Applying Definitions to the Goal

We begin with an simple example, proving that the length of an empty list is 0. Of course, this is a direct consequence of the definition of length, so this first example is about how to use definitions. To get started, we write down the theorem we would like to prove. A theorem starts with a label, followed by a colon, then the formula followed by the proof. But instead of writing the proof, we’ll simply write ? to say that we’re not done yet.

theorem length_nat_empty: length(@[]<Nat>) = 0
proof
  ?
end

Run Deduce on the file. Deduce will respond with the following message to remind us of what is left to prove.

incomplete proof:
    length([]) = 0

To tell Deduce to apply the definition of length, we can use the definition statement.

theorem length_nat_empty: length(@[]<Nat>) = 0
proof
  definition length
end

Deduce expanded the definition of length in the goal, changing length([]) = 0 to 0 = 0. In particular, Deduce noticed that length([]) matches the first clause in the definition of length and then replaced it with the right-hand side of the first clause. Deduce then simplified 0 = 0 to true and therefore accepted the definition statement. In general, whenever Deduce sees an equality with the same left and right-hand side, it automatically simplifies it to true.

Run Deduce on the file to see it respond that the file is valid.

Let’s try a slightly more complex theorem, that the length of a list with just a single node is indeed 1. Based on what we learned above, we might try using the definition of length.

theorem length_node42: length([42]) = 1
proof
  definition length
end

Deduce responds with

failed to prove:
    length([42]) = 1
by
    definition {length}
remains to prove:
    1 + length([]) = 1

It is quite common to apply a definition and then need to prove the remaining goal. Deduce provides the suffices statement for this purpose. The suffices keyword is followed by the new goal formula, then the keyword with, followed by a definition statement. However, it’s easiest to let Deduce figure out the new goal formula, so to start you can use ? as the goal formula.

theorem length_node42: length([42]) = 1
proof
  suffices ? 
      by definition length
  ?
end

Deduce responds with

suffices to prove:
    1 + length([]) = 1

We need to apply the definition of length again to simplify length(empty), so we add another length to the definition statement.

theorem length_node42: length([42]) = 1
proof
  suffices ? 
      by definition {length, length}
  ?
end

Deduce responds this time with

suffices to prove:
    1 + 0 = 1

Which is a nice formula to use for the suffices. So we cut and paste that to replace the ?.

theorem length_node42: length([42]) = 1
proof
  suffices 1 + 0 = 1 
      by definition {length, length}
  ?
end

Finally we need to prove, 1 + 0 = 1. That can be proved using the add_zero theorem from the file Nat.pf, which we explain in the upcoming section on Reasoning about Natural Numbers.

theorem length_node42: length([42]) = 1
proof
  suffices 1 + 0 = 1
      by definition {length, length}
  add_zero[1]
end

Exercise

Prove that [1] ++ [2] = [1, 2] by filling in the ? below.

theorem append_node_1_node_2:
  [1] ++ [2] = [1, 2]
proof
  ?
end

Generalizing with all formulas

In the proof of length_node42 it did not matter that the element in the node was 42. We can generalize this theorem by using an all formula. We begin the formula with all x:Nat. to say that the formula must be true for all natural numbers and the variable x will be used to refer to the natural number. We then replace the 42 in the formula with x to obtain the following theorem statement.

theorem length_one_nat: all x:Nat. length([x]) = 1
proof
  ?
end

Deduce responds with

incomplete proof:
    all x:Nat. length([x]) = 1

The most straightforward way to prove an all formula in Deduce is with an arbitrary statement. When you use arbitrary you are promising to prove the formula for a hypothetical entity that can stand in for all entities of the specified type. The arbitrary statement asks you to name the hypothetical entity. Here we choose x but we could have chosen a different name.

theorem length_one_nat: all x:Nat. length([x]) = 1
proof
  arbitrary x:Nat
  ?
end

Deduce responds with

incomplete proof:
    length([x]) = 1

We don’t know anything about this hypothetical x other than it being a natural number. But as we previously observed, we don’t need any more information about x in this example. We complete the proof as before, using the definitions of length and the add_zero theorem.

theorem length_one_nat: all x:Nat. length([x]) = 1
proof
  arbitrary x:Nat
  suffices 1 + 0 = 1
      by definition {length, length}
  add_zero[1]
end

Once we have proved that an all formula is true, we can use it by supplying an entity of the appropriate type inside square brackets. In the following we prove the length_node42 theorem again, but this time the proof makes use of length_one_nat.

theorem length_node42_again: length([42]) = 1
proof
  length_one_nat[42]
end

We can generalize the theorem yet again by noticing that it does not matter whether the element is a natural number. It could be a value of any type. In Deduce we can also use the all statement to generalize types. In the following, we add all U:type to the formula and another arbitrary statement.

theorem length_one: all U:type. all x:U. length([x]) = 1
proof
  arbitrary U:type
  arbitrary x:U
  suffices 1 + 0 = 1
      by definition {length, length}
  add_zero[1]
end

To summarize this section:

Exercise

Complete the following proof. 

theorem append_xy:
  all T:type. all x:T, y:T. [x] ++ [y] = [x, y]
proof
  ?
end

Prove again that

[1] ++ [2] = [1, 2]

but this time use the previous theorem.

Rewriting the Goal with Equations

Deduce provides the rewrite statement to apply an equation to the current goal. In particular, rewrite replaces each occurence of the left-hand side of an equation with the right-hand side of the equation.

For example, let us prove the following theorem using rewrite with the above length_one theorem.

theorem length_one_equal: all U:type. all x:U, y:U.
  length([x]) = length([y])
proof
  arbitrary U:type
  arbitrary x:U, y:U
  ?
end

To replace length([x]) with 1, we rewrite using the length_one theorem instantiated at U and x. Note that we use < and > when instantiating a type parameter and we use [ and ] when instantiating a term parameter.

rewrite length_one<U>[x]

Deduce tells us that the current goal has become

remains to prove:
	1 = length([y])

We rewrite again, separated by a vertical bar, using length_one, this time instantiated with y.

rewrite length_one<U>[x] | length_one<U>[y]

Deduce changes the goal to 1 = 1, which simplies to just true, so Deduce accepts the rewrite statement.

Here is the completed proof of length_one_equal.

theorem length_one_equal: all U:type. all x:U, y:U.
  length([x]) = length([y])
proof
  arbitrary U:type
  arbitrary x:U, y:U
  rewrite length_one<U>[x] | length_one<U>[y]
end

Reasoning about Natural Numbers

The Nat.pf file includes the definition of natural numbers, operations on them (e.g. addition), and proofs about those operations. Also, Deduce automatically generates a summary of the theorems and puts them in the file Nat.thm.

Here we discuss how to reason about addition. Reasoning about the other operations follows a similar pattern.

Here is the definition of natural numbers from Nat.pf: 

union Nat {
  zero
  suc(Nat)
}

The parser for Deduce translates 0 into zero, 1 into suc(zero), 2 into suc(suc(zero)), and so on.

Here is the definition of addition from Nat.pf:

function operator +(Nat,Nat) -> Nat {
  operator +(0, m) = m
  operator +(suc(n), m) = suc(n + m)
}

Recall that we can use Deduce’s definition statement whenever we want to rewrite the goal according to the equations for addition. Here are the two defining equations, but written with infix notation:

  0 + m = m
  suc(n) + m = suc(n + m)

The Nat.pf file also includes proofs of many equations. Here we list the names of the theorems and the formula. (To add more theorems, pull requests on the github repository are most welcome!)

add_zero: all n:Nat.  n + 0 = n
add_commute: all n:Nat. all m:Nat.  n + m = m + n
add_assoc: all m:Nat. all n:Nat, o:Nat.  (m + n) + o = m + (n + o)
left_cancel: all x:Nat. all y:Nat, z:Nat.  if x + y = x + z then y = z
add_to_zero: all n:Nat. all m:Nat. if n + m = 0 then n = 0 and m = 0
dist_mult_add: all a:Nat. all x:Nat, y:Nat. a * (x + y) = a * x + a * y
mult_zero: all n:Nat. n * 0 = 0
mult_one: all n:Nat. n * 1 = n
mult_commute: all m:Nat. all n:Nat. m * n = n * m
mult_assoc: all m:Nat. all n:Nat, o:Nat. (m * n) * o = m * (n * o)

You can use these theorems by instantiating them with particular entities. For example, add_zero[2] is a proof of 2 + 0 = 2. We have not yet discussed how to use the if-then formula in left_cancel, but we will get to that in the section below on Conditional Formulas (Implication).

Exercise

Prove the following theorem using the add_zero and mult_one theorems from Nat.pf.

theorem x_0_x_eq_2_x: 
  all x:Nat. (x + 0) + x = (x + x) * 1
proof
  ?
end

Proving Intermediate Facts with have

One often needs to prove some intermediate facts on the way to proving the final goal of a theorem. The have statement of Deduce provides a way to state and prove a fact and give it a label so that it can be used later in the proof. For example, consider the proof of

x + y + z = z + y + x

It takes several uses of add_commute and add_assoc to prove this. To get started, we use have to give the label step1 to a proof of x + y + z = x + z + y (flipping the y and z).

theorem xyz_zyx: all x:Nat, y:Nat, z:Nat.
  x + y + z = z + y + x
proof
  arbitrary x:Nat, y:Nat, z:Nat
  have step1: x + y + z = x + z + y
    by rewrite add_commute[y][z]
  ?
end

Deduce prints the current goal and the givens, that is, the formulas that we aleady know are true, which now includes step1.

incomplete proof
Goal:
	x + (y + z) = z + (y + x)
Givens:
	step1: x + (y + z) = x + (z + y)

We proceed four more times, using have to create each intermediate step in the reasoning.

  have step2: x + z + y = (x + z) + y
    by rewrite add_assoc[x][z,y]
  have step3: (x + z) + y = (z + x) + y
    by rewrite add_commute[z][x]
  have step4: (z + x) + y = z + (x + y)
    by rewrite add_assoc[z][x,y]
  have step5: z + (x + y) = z + y + x
    by rewrite add_commute[x][y]

We finish the proof by connecting them all together using Deduce’s transitive statement. The transitive statement takes two proofs of equations a = b and b = c, and proves a = c. Here we use the intermediate facts step1, step2, etc. by referencing their label. In general, to use one of the given facts, one just needs to use its label.

  transitive step1 (transitive step2 (transitive step3
    (transitive step4 step5)))

Here is the complete proof of the xyz_zyx theorem.

theorem xyz_zyx: all x:Nat, y:Nat, z:Nat.
  x + y + z = z + y + x
proof
  arbitrary x:Nat, y:Nat, z:Nat
  have step1: x + y + z = x + z + y
    by rewrite add_commute[y][z]
  have step2: x + z + y = (x + z) + y
    by rewrite add_assoc[x][z,y]
  have step3: (x + z) + y = (z + x) + y
    by rewrite add_commute[z][x]
  have step4: (z + x) + y = z + (x + y)
    by rewrite add_assoc[z][x,y]
  have step5: z + (x + y) = z + y + x
    by rewrite add_commute[x][y]
  transitive step1 (transitive step2 (transitive step3
    (transitive step4 step5)))
end

Chaining Equations with equations

Combining a sequence of equations using transitive is quite common, so Deduce provides the equations statement to streamline this process. After the first equation, the left-hand side of each equation is written as ... because it is just a repetition of the right-hand side of the previous equation. Here’s another proof of the theorem about x + y + z, this time using an equations statement.

theorem xyz_zyx_eqn: all x:Nat, y:Nat, z:Nat.
  x + y + z = z + y + x
proof
  arbitrary x:Nat, y:Nat, z:Nat
  equations
    x + y + z = x + z + y      by rewrite add_commute[y][z]
          ... = (x + z) + y    by rewrite symmetric add_assoc[x][z,y]
          ... = (z + x) + y    by rewrite symmetric add_commute[z][x]
          ... = z + x + y      by rewrite add_assoc[z][x,y]
          ... = z + y + x      by rewrite add_commute[x][y]
end

The equations feature is implemented in Deduce by translating them into a bunch of transitive statements.

Exercise

Prove that x + y + z = z + y + x but using fewer than 5 steps.

Proving all Formulas with Induction

Sometimes the arbitrary statement does not give us enough information to prove an all formula. In those situations, so long as the type of the all variable is a union type, we can use the more powerful induction statement.

For example, consider the following theorem about appending a list to an empty list. Suppose we try to use arbitrary for both the all U and the all xs.

theorem append_empty: all U :type. all xs :List<U>.
  xs ++ [] = xs
proof
  arbitrary U:type
  arbitrary xs:List<U>
  ?
end

Deduce replies that we need to prove

incomplete proof:
    xs ++ [] = xs

But now we’re stuck because the definition of append pattern matches on its first argument, but we don’t know whether xs is an empty list or a node.

So instead of using arbitrary xs:List<U> to prove the all xs, we proceed by induction as follows.

theorem append_empty: all U :type. all xs :List<U>.
  xs ++ [] = xs
proof
  arbitrary U:type
  induction List<U>
  case empty {
    ?
  }
  case node(n, xs') suppose IH: xs' ++ [] = xs' {
    ?
  }
end

When doing a proof by induction, there is one case for every alternative in the union type. Here the union type is List<U>, so we have a case for the empty and node alternatives. Furthermore, because node includes a recursive argument, that is, and argument of type List<U>, in the case for node we get to assume that the formula we are trying to prove is already true for the argument. This is commonly known at the induction hypothesis. We must give a label for the induction hypothesis so here we choose IH for short.

Let us first focus on the case for empty. Deduce tells us that we need to prove the following.

incomplete proof:
    [] ++ [] = []

This follows directly from the definition of append.

case empty {
  definition operator++
}

However, to make the proof more readable by other humans, I recommend restating the goal using the conclude statement.

case empty {
  conclude @[]<U> ++ [] = []  by definition operator++
}

Next let us focus on the case for node. Deduce tells us that we need to prove the following and that IH has been added to the available facts.

incomplete proof:
    node(n,xs') ++ [] = node(n,xs')

available facts:
    IH: xs' ++ [] = xs',
    ...

Looking at the goal, we notice that we can expand the definition of ++ on the right-hand side, because it is applied to a node. Perhaps we forget the exact definition of ++, so we can let Deduce tell us the expansion by putting ? on the right-hand side of the equation.

case node(n, xs') suppose IH: xs' ++ [] = xs' {
  equations
    node(n,xs') ++ []
        = ?                       by definition operator++
    ... = node(n,xs')             by ?
}

Deduce responds with

remains to prove:
    node(n, xs' ++ []) = ?

It has transformed the left-hand side of the equation by expanding the definition of ++. We copy and paste the node(n, xs' ++ empty) to replace the ?.

case node(n, xs') suppose IH: xs' ++ [] = xs' {
  equations
    node(n,xs') ++ []
        = node(n, xs' ++ [])   by definition operator++
    ... = node(n,xs')             by ?
}

Next, we see that the subterm xs' ++ [] matches the right-hand side of the induction hypothesis IH. We use the rewrite statement to apply the IH equation to this subterm.

case node(n, xs') suppose IH: xs' ++ [] = xs' {
  equations
    node(n,xs') ++ []
        = node(n, xs' ++ [])   by definition operator++
    ... = node(n,xs')             by rewrite IH
}

Here is the completed proof of append_empty.

theorem append_empty: all U :type. all xs :List<U>.
  xs ++ [] = xs
proof
  arbitrary U:type
  induction List<U>
  case empty {
    conclude @[]<U> ++ [] = []  by definition operator++
  }
  case node(n, xs') suppose IH: xs' ++ [] = xs' {
    equations
      node(n,xs') ++ []
          = node(n, xs' ++ [])   by definition operator++
      ... = node(n,xs')             by rewrite IH
  }
end

To summarize this section:

Exercise

Fill in the proof of the following theorem about length and ++.

theorem length_append: all U :type. all xs :List<U>. all ys :List<U>.
  length(xs ++ ys) = length(xs) + length(ys)
proof
  ?
end

Reasoning about and (Conjunction)

To create a single formula that expresses that two formulas are true, combine the two formulas with and (i.e. conjunction). The following example proves that 0 ≤ 1 and 0 ≤ 2. This is accomplished by separately proving that 0 ≤ 1 is true and that 0 ≤ 2 is true, then using the comma operator to combine those proofs: one_pos, two_pos.

theorem positive_1_and_2: 0 ≤ 1 and 0 ≤ 2
proof
  have one_pos: 0 ≤ 1 by definition operator ≤
  have two_pos: 0 ≤ 2 by definition operator ≤
  conclude 0 ≤ 1 and 0 ≤ 2 by one_pos, two_pos
end

On the other hand, in Deduce you can use a conjunction as if it were one of its subformulas, implicitly. In the following we use the fact that 0 ≤ 1 and 0 ≤ 2 to prove 0 ≤ 2.

theorem positive_2: 0 ≤ 2
proof
  conclude 0 ≤ 2 by positive_1_and_2
end

To summarize this section:

Reasoning about or (Disjunction)

Two create a formula that expresses that at least one of two formulas is true (i.e. disjunction), use or to combine the formulas.

For example, consider the following variation on the trichotomy law for numbers, which states that for any two natural numbers x and y, either x ≤ y or y < x.

theorem dichotomy:  all x:Nat, y:Nat.  x ≤ y  or  y < x
proof
  ?
end

We can prove this using the trichotomy theorem from Nat.pf, which tells us that x < y or x = y or y < x.

theorem dichotomy:  all x:Nat, y:Nat.  x ≤ y  or  y < x
proof
  arbitrary x:Nat, y:Nat
  have tri: x < y or x = y or y < x by trichotomy[x][y]
  ?
end

In Deduce, you can use an or fact by doing case analysis with the cases statement. There is one case for each subformula of the or.

have tri: x < y or x = y or y < x by trichotomy[x][y]
cases tri
case x_l_y: x < y {
  ?
}
case x_eq_y: x = y {
  ?
}
case y_l_x: y < x {
  ?
}

In the first case, we consider the situation where x < y and still need to prove that x ≤ y or y < x. Thankfully, the theorem less_implies_less_equal in Nat.pf tells us that x ≤ y.

case x_l_y: x < y {
  have x_le_y: x ≤ y by apply less_implies_less_equal[x][y] to x_l_y
  ?
}

In Deduce, an or formula can be proved using a proof of either subformula, so here we prove x ≤ y or y < x with x ≤ y.

case x_l_y: x < y {
  have x_le_y: x ≤ y by apply less_implies_less_equal[x][y] to x_l_y
  conclude x ≤ y or y < x by x_le_y
}

In the second case, we consider the situation where x = y. Here we can prove that x ≤ y by rewriting the x to y and then using the reflexive property of the less-equal relation to prove that y ≤ y.

case x_eq_y: x = y {
  have x_le_y: x ≤ y by
      suffices y ≤ y  by rewrite x_eq_y
      less_equal_refl[y]
  conclude x ≤ y or y < x by x_le_y
}

In the third case, we consider the situation where y < x. So we can immediately conclude that x ≤ y or y < x.

case y_l_x: y < x {
  conclude x ≤ y or y < x by y_l_x
}

Here is the completed proof of the dichotomy theorem.

theorem dichotomy:  all x:Nat, y:Nat.  x ≤ y  or  y < x
proof
  arbitrary x:Nat, y:Nat
  have tri: x < y or x = y or y < x by trichotomy[x][y]
  cases tri
  case x_l_y: x < y {
    have x_le_y: x ≤ y by apply less_implies_less_equal[x][y] to x_l_y
    conclude x ≤ y or y < x by x_le_y
  }
  case x_eq_y: x = y {
    have x_le_y: x ≤ y by
        suffices y ≤ y  by rewrite x_eq_y
        less_equal_refl[y]
    conclude x ≤ y or y < x by x_le_y
  }
  case y_l_x: y < x {
    conclude x ≤ y or y < x by y_l_x
  }
end

To summarize this section:

The switch Proof Statement

Similar to Deduce’s switch statement for writing functions, there is also a switch statement for writing proofs. As an example, let us consider how to prove the following theorem.

theorem zero_or_positive: all x:Nat. x = 0 or 0 < x
proof
  ?
end

We could proceed by induction, but it turns out we don’t need the induction hypothesis. In such situations, we can instead use switch. Like induction, switch works on unions and there is one case for each alternative of the union. Unlike induction, the goal formula does not need to be an all formula. Instead, you indicate which entity to switch on, as in switch x below.

arbitrary x:Nat
switch x {
  case zero {
    ?
  }
  case suc(x') {
    ?
  }
}

Deduce responds that in the first case we need to prove the following.

incomplete proof:
    true or 0 < 0

So we just need to prove true, which is what the period is for.

case zero {
  conclude true or 0 < 0 by .
}

In the second case, for x = suc(x'), we need to prove the following.

incomplete proof:
    false or 0 < suc(x')

There’s no hope of proving false, so we better prove 0 < suc(x'). Thankfully that follows from the definitions of < and ≤.

case suc(x') {
  have z_l_sx: 0 < suc(x') by definition {operator <, operator ≤}
  conclude suc(x') = 0 or 0 < suc(x') by z_l_sx
}

Here is the completed proof that every natural number is either zero or positive.

theorem zero_or_positive: all x:Nat. x = 0 or 0 < x
proof
  arbitrary x:Nat
  switch x {
    case zero {
      conclude true or 0 < 0 by .
    }
    case suc(x') {
      have z_l_sx: 0 < suc(x') by definition {operator <, operator ≤, operator ≤}
      conclude suc(x') = 0 or 0 < suc(x') by z_l_sx
    }
  }
end

To summarize this section:

Applying Definitions and Rewrites to the Goal

Sometimes one needs to apply a set of definitions and rewrites to the goal. Consider the following definition of max'. (There is a different definition of max in Nat.pf.)

define max' = λx:Nat, y:Nat { if x ≤ y then y else x }

To prove that x ≤ max'(x,y) we consider two cases, whether x ≤ y or not. If x ≤ y is true, we apply the definition of max' and we rewrite with the fact that x ≤ y is true, which resolves the if-then-else inside of max' to just y.

    suffices x ≤ y  by definition max' and rewrite x_le_y_true

So we are left to prove that x ≤ y, which we already know. Similarly, if x ≤ y is false, we apply the definition of max' and rewrite with the fact that x ≤ y is false.

    suffices x ≤ x  by definition max' and rewrite x_le_y_false

This resolves the if-then-else inside of max' to just x. So we are left to prove x ≤ x, which of course is true. Here is the complete proof that x ≤ max'(x,y).

theorem less_max: all x:Nat, y:Nat.  x ≤ max'(x,y)
proof
  arbitrary x:Nat, y:Nat
  switch x ≤ y {
    case true suppose x_le_y_true {
      suffices x ≤ y  by definition max' and rewrite x_le_y_true
      rewrite x_le_y_true
    }
    case false suppose x_le_y_false {
      suffices x ≤ x  by definition max' and rewrite x_le_y_false
      less_equal_refl[x]
    }
  }
end

Conditional Formulas (Implication) and Applying Definitions to Facts

Some logical statements are true only under certain conditions, so Deduce provides an if-then formula. To demonstrate how to work with if-then formulas, we prove that if a list has length zero, then it must be the empty list. Along the way we will also learn how to apply a definition to an already-known fact.

theorem length_zero_empty: all T:type. all xs:List<T>.
  if length(xs) = 0 then xs = []
proof
  arbitrary T:type
  arbitrary xs:List<T>
  ?
end

Deduce tells us:

incomplete proof
Goal:
	(if length(xs) = 0 then xs = [])

To prove an if-then formula, we suppose the condition and then prove the conclusion.

  suppose len_z: length(xs) = 0

Deduce adds len_z to the givens (similar to have).

incomplete proof
Goal:
	xs = []
Givens:
	len_z: length(xs) = 0

Next we switch on the list xs. In the case when xs is empty it will be trivial to prove xs = []. In the other case, we will obtain a contradiction.

  switch xs {
    case empty { . }
    case node(x, xs') suppose xs_xxs: xs = node(x,xs') {
      ?
    }
  }

We can put the facts len_z and xs_xxs together to obtain the dubious looking length(node(x,xs')) = 0.

	have len_z2: length(node(x,xs')) = 0  by rewrite xs_xxs in len_z

The contradiction becomes apparent to Deduce once we apply the definition of length to this fact. We do so using Deduce’s definition-in statement as follows.

    conclude false  by definition length in len_z2

We discuss contradictions and false in more detail in the upcoming section Reasoning about false.

Here is the complete proof of length_zero_empty.

theorem length_zero_empty: all T:type. all xs:List<T>.
  if length(xs) = 0 then xs = []
proof
  arbitrary T:type
  arbitrary xs:List<T>
  suppose len_z: length(xs) = 0
  switch xs {
    case empty { . }
    case node(x, xs') suppose xs_xxs: xs = node(x,xs') {
	  have len_z2: length(node(x,xs')) = 0  by rewrite xs_xxs in len_z
      conclude false  by apply not_one_add_zero[length(xs')]
                         to definition length in len_z2
    }
  }
end

The next topic to discuss is how to use an if-then fact that is already proven. We use Deduce’s apply-to statement (aka. modus ponens) to obtain the conclusion of an if-then formula by supplying a proof of the condition. We demonstrate several uses of apply-to in the proof of the following theorem, which builds on length_zero_empty.

theorem length_append_zero_empty: all T:type. all xs:List<T>, ys:List<T>.
  if length(xs ++ ys) = 0
  then xs = [] and ys = []
proof
  arbitrary T:type
  arbitrary xs:List<T>, ys:List<T>
  suppose len_xs_ys: length(xs ++ ys) = 0
  ?
end

Recall that in a previous exercise, you proved that

length(xs ++ ys) = length(xs) + length(ys)

so we can prove that length(xs) + length(ys) = 0 as follows.

  have len_xs_len_ys: length(xs) + length(ys) = 0
    by transitive (symmetric length_append<T>[xs][ys]) len_xs_ys

Note that Deduce’s the symmetric statement takes a proof of some equality like a = b and flips it around to b = a.

Now from Nat.pf we have the following if-then fact.

add_to_zero: all n:Nat. all m:Nat. if n + m = 0 then n = 0 and m = 0

Here is our first use of apply-to to obtain length(xs) = 0 and the same for ys. (Deduce can infer the arguments for the all n and all m in add_to_zero.)

  have len_xs: length(xs) = 0  by apply add_to_zero to len_xs_len_ys
  have len_ys: length(ys) = 0  by apply add_to_zero to len_xs_len_ys

We conclude that xs = empty and ys = empty with our second use of apply-to, where we make use of the previous theorem length_zero_empty.

  conclude xs = empty and ys = empty
  by (apply length_zero_empty<T>[xs] to len_xs),
     (apply length_zero_empty<T>[ys] to len_ys)

Here is the complete proof of length_append_zero_empty.

theorem length_append_zero_empty: all T:type. all xs:List<T>, ys:List<T>.
  if length(xs ++ ys) = 0
  then xs = [] and ys = []
proof
  arbitrary T:type
  arbitrary xs:List<T>, ys:List<T>
  suppose len_xs_ys: length(xs ++ ys) = 0
  have len_xs_len_ys: length(xs) + length(ys) = 0
    by transitive (symmetric length_append<T>[xs][ys]) len_xs_ys
  have len_xs: length(xs) = 0  by apply add_to_zero to len_xs_len_ys
  have len_ys: length(ys) = 0  by apply add_to_zero to len_xs_len_ys
  conclude xs = [] and ys = []
  by (apply length_zero_empty<T>[xs] to len_xs),
     (apply length_zero_empty<T>[ys] to len_ys)
end

To summarize this section:

Exercise

Prove that all x:Nat. if x ≤ 0 then x = 0.

Reasoning about true

There’s not much to say about true. It’s true! And as we’ve already seen, proving true is easy. Just use a period.

theorem really_trivial: true
proof
  .
end

One almost never sees true written explicitly in a formula. However, it is common for a formula to simplify to true after some rewriting.

Reasoning about false

The formula false is also rarely written explicitly in a formula. However, it can arise in contradictory situations. For example, in the following we have a situation in which true = false. That can’t be, so Deduce simplifies true = false to just false.

theorem contra_false: all a:bool, b:bool.
  if a = b and a = true and b = false then false
proof
  arbitrary a:bool, b:bool
  suppose prem: a = b and a = true and b = false
  have a_true: a = true by prem
  have b_true: b = false by prem
  conclude false by rewrite a_true | b_true in prem
end

More generally, Deduce knows that the different constructors of a union are in fact different. So in the next example, because foo and bar are different constructors, Deduce simplifies foo = bar to false.

union U {
  foo
  bar
}

theorem foo_bar_false: if foo = bar then false
proof
  .
end

The above proof is just a period because Deduce simplifies any formula of the form if false then ... to true, which is related to our next point.

So far we’ve discussed how a proof of false can arise. Next let’s talk about how you can use false once you’ve got it. The answer is anything! The Principle of Explosion from logic tells us that false implies anything. For example, normally we don’t know whether or not two arbitrary Booleans x and y are the same or different. But if we have a premise that is false, it doesn’t matter.

theorem false_any: all x:bool, y:bool. if false then x = y
proof
  arbitrary x:bool, y:bool
  suppose f: false
  conclude x = y by f
end

To summarize this section:

Reasoning about not

To express that a formula is false, precede it with not. For example, for any natural number x, it is not the case that x < x.

theorem less_irreflexive:  all x:Nat. not (x < x)
proof
  ?
end

We proceed by induction.

induction Nat
case zero {
  ?
}
case suc(x') suppose IH: not (x' < x') {
  ?
}

Deduce treats not as syntactic sugar for a conditional formal with a false conclusion. So in the first case, we must prove that 0 < 0 implies false. So we suppose the premise 0 < 0 and then conclude false by the definitions of < and ≤.

case zero {
  suppose z_l_z: 0 < 0
  conclude false by definition {operator <, operator ≤} in z_l_z
}

In the case where x = suc(x'), we must prove that suc(x') < suc(x') implies false. So we assume the premise suc(x') < suc(x') from which we can prove that x' < x' using the definitions of < and ≤.

suppose sx_l_sx: suc(x') < suc(x')
enable {operator <, operator ≤}
have x_l_x: x' < x' by sx_l_sx

We conclude this case by applying the induction hypothesis to x' < x'.

conclude false by apply IH to x_l_x

Here is the completed proof that less-than is irreflexive.

theorem less_irreflexive:  all x:Nat. not (x < x)
proof
  induction Nat
  case zero {
    suppose z_l_z: 0 < 0
    conclude false by definition {operator <, operator ≤} in z_l_z
  }
  case suc(x') suppose IH: not (x' < x') {
    suppose sx_l_sx: suc(x') < suc(x')
    enable {operator <, operator ≤}
    have x_l_x: x' < x' by sx_l_sx
    conclude false by apply IH to x_l_x
  }
end

To summarize this section:

Rewriting Facts with Equations

In the section Rewriting the Goal with Equations we learned that the rewrite statement of Deduce applies an equation to the current goal. There is a second variant of rewrite that applies an equation to a fact. As an example, we’ll prove the following theorem that is a straightforward use of less_irreflexive.

theorem less_not_equal: all x:Nat, y:Nat.
  if x < y then not (x = y)
proof
  arbitrary x:Nat, y:Nat
  suppose x_l_y: x < y
  ?
end

Deduce responds with the current goal, in which not (x = y) is expanding into if x = y then false.

incomplete proof
Goal:
	(if x = y then false)
Givens:
	x_l_y: x < y

So following the usual recipte to prove an if-then, we suppose the condition x = y.

  suppose x_y: x = y

Now we need to prove false, and we have the hint to use the less_irreflexive theorem.

incomplete proof
Goal:
	false
Givens:
	x_y: x = y,
	x_l_y: x < y

Here is where the second variant of rewrite comes in. We can use it to apply the equation x = y to the fact x < y to get y < y. Note the extra keyword in that is used in this version of rewrite.

  have y_l_y: y < y   by rewrite x_y in x_l_y

We arrive at the contradition by applying less_irreflexive to y < y.

  conclude false by apply less_irreflexive[y] to y_l_y

Here is the complete proof of less_not_equal.

theorem less_not_equal: all x:Nat, y:Nat.
  if x < y then not (x = y)
proof
  arbitrary x:Nat, y:Nat
  suppose x_l_y: x < y
  suppose x_y: x = y
  have y_l_y: y < y by rewrite x_y in x_l_y
  conclude false by apply less_irreflexive[y] to y_l_y
end

Exercise

Using the rewrite-in statement, prove the following variation on the transitivity theorem for ≤. Prove that if x = y and y ≤ z, then x ≤ z.

theorem equal_less_trans: all x:Nat, y:Nat, z:Nat.
  if x = y and y ≤ z then x ≤ z
proof
  ?
end

Reasoning about some (Exists) and asking for help

In Deduce, you can express that there is at least one entity that satisfies a given property using the some formula. For example, one way to define an even number is to say that it is a number that is 2 times some other number. We express this in Deduce as follows.

define Even = λ n:Nat { some m:Nat. n = 2 * m }

As an example of how to reason about some formulas, let us prove a classic property of the even numbers, that the addition of two even numbers is an even number. Here’s the beginning of the proof.

theorem addition_of_evens:
  all x:Nat, y:Nat.
  if Even(x) and Even(y) then Even(x + y)
proof
  arbitrary x:Nat, y:Nat
  suppose even_xy: Even(x) and Even(y)
  have even_x: some m:Nat. x = 2 * m by definition Even in even_xy
  have even_y: some m:Nat. y = 2 * m by definition Even in even_xy
  ?
end

The next step in the proof is to make use of the facts even_x and even_y. We can ask Deduce for help in how to use a given with the help feature.

help even_x

Deduce responds with

Advice about using fact:
some m:Nat. x = 2 * m

Proceed with:
	obtain A where label: x = 2 * A from even_x
where A is a new name of your choice

So we go ahead and write two obtain statements, one for even_x and another for even_y, making different choices to replace the variable A in the above advice.

obtain a where x_2a: x = 2*a from even_x
obtain b where y_2b: y = 2*b from even_y

Deduce responds with

available facts:
    y_2b: y = 2 * b,
    x_2a: x = 2 * a,

The a and b are new variables and the two facts y_2b and x_2a are the subformulas of the some, but with a and b replacing m.

We still need to prove the following:

incomplete proof:
    Even(x + y)

So we use the definition of Even in a suffices statement

suffices some m:Nat. x + y = 2 * m  by definition Even
?

To prove a some formula, we use Deduce’s choose statement. This requires some thinking on our part. What number can we plug in for m such that doubling it is equal to x + y? Given what we know about a and b, the answer is a + b. We conclude the proof by using the equations for x and y and the distributivity property of multiplication over addition (from Nat.pf).

choose a + b
suffices 2 * a + 2 * b = 2 * (a + b)  by rewrite x_2a | y_2b
symmetric dist_mult_add[2][a,b]

Here is the complete proof.

theorem addition_of_evens:
  all x:Nat, y:Nat.
  if Even(x) and Even(y) then Even(x + y)
proof
  arbitrary x:Nat, y:Nat
  suppose even_xy: Even(x) and Even(y)
  have even_x: some m:Nat. x = 2 * m by definition Even in even_xy
  have even_y: some m:Nat. y = 2 * m by definition Even in even_xy
  obtain a where x_2a: x = 2*a from even_x
  obtain b where y_2b: y = 2*b from even_y
  suffices some m:Nat. x + y = 2 * m  by definition Even
  choose a + b
  suffices 2 * a + 2 * b = 2 * (a + b)  by rewrite x_2a | y_2b
  symmetric dist_mult_add[2][a,b]
end

To summarize this section: