"Algorithms are the computational content of proofs." (Robert Harper)

Programming with Propositions

Note to readers: Some of the concepts in this chapter may seem quite abstract on a first encounter. We've included a lot of exercises, most of which should be quite approachable even if you're still working on understanding the details of the text. Try to work as many of them as you can, especially the one-starred exercises. So far, the only statements we have been able to state and prove have been in the form of equalities. However, the language of mathematical statements and proofs is much richer than this! In this chapter we will take a much closer and more fundamental look at the sorts of mathematical statements (propositions) we can make in Coq, and how we go about proving them by providing logical evidence. A proposition is a statement expressing a factual claim, like "two plus two equals four." In Coq, propositions are written as expressions of type Prop. Although we haven't mentioned it explicitly, we have already seen numerous examples.

Both provable and unprovable claims are perfectly good propositions. Simply being a proposition is one thing; being provable is something else!

Both 2 + 2 = 4 and 2 + 2 = 5 are legal expressions of type Prop. We've seen one way that propositions can be used in Coq: in Theorem (and Lemma and Example) declarations.

But they can be used in many other ways. For example, we can give a name to a proposition using a Definition, just as we have given names to expressions of other sorts (numbers, functions, types, type functions, ...).

Now we can use this name in any situation where a proposition is expected — for example, as the claim in a Theorem declaration.

So far, all the propositions we have seen are equality propositions. We can also form new propositions out of old ones. For example, given propositions P and Q, we can form the proposition "P implies Q."

Also, given a proposition P with a free variable n, we can form the proposition ∀ n, P.

Finally, we can define parameterized propositions. For example, what does it mean to claim that "a number n is even"? We have written a function that tests evenness, so one possible definition of what it means to be even is "n is even iff evenb n = true."

This defines even as a function that, when applied to a number n, yields a proposition asserting that n is even.

The type of even, nat→Prop, can be pronounced in three ways: (1) "even is a function from numbers to propositions," (2) "even is a family of propositions, indexed by a number n," or (3) "even is a property of numbers." Propositions — including parameterized propositions — are first-class citizens in Coq. We can use them in other definitions:

We can define them to take multiple arguments...

... and then partially apply them:

We can even pass propositions — including parameterized propositions — as arguments to functions:

(Names of the form x__y, with two underscores in a row, can be read "x implies y.") Here are two more examples of passing parameterized propositions as arguments to a function. The first makes the claim that a whenever a proposition P is true for some natural number n', it is also true by the successor of n':

And this one simply claims that a proposition is true for all natural numbers:

We can put these pieces together to manually restate the principle of induction for natural numbers. Given a parameterized proposition P, if P is true for 0, and P (S n') is true whenever P n' is, then P is true for all natural numbers.

Evidence

We've seen that well-formed expressions of type Prop can embody both provable and unprovable propositions. Naturally, we're particularly interested in the provable ones. When P is a proposition and e is a proof of P — i.e., e is evidence that P is true — we'll write "e : P." This overloading of the "has type" or "inhabits" notation is not accidental: we'll see that there is a fundamental and fruitful analogy between data values inhabiting types and evidence "inhabiting" propositions. The next question is "what are proofs?" — i.e., what sorts of things would we be willing to accept as evidence that particular propositions are true?

Inductively Defined Propositions

The answer, of course, depends on the form of the proposition — evidence for implication propositions (P→Q) is different from evidence for conjunctions (P∧Q), etc. In this chapter and the next, we'll address a number of specific cases. To begin with, consider atomic propositions — ones that aren't built into the logic we're using, but are rather introduced to model useful concepts in a particular domain. For example, having defined a type day as we did in Basics.v, we might have some concept in our minds about certain days, say the fact that saturday and sunday are "good" ones. If we want to use Coq to state and prove theorems involving good days, we need to begin by telling it what we mean by "good" — that is, we need to specify what counts as as evidence that some day d is good (namely, that d is either saturday or sunday. The following declaration achieves this:

The Inductive keyword means exactly the same thing whether we are using it to define sets of data values (in the Type world) or sets of evidence (in the Prop world). Consider the parts of the definition above:

• The first line declares that good_day is a proposition indexed by a day.
• The second line declares that the constructor gd_sat can be taken as evidence for the assertion good_day saturday.
• The third line declares that the constructor gd_sun can be taken as evidence for the assertion good_day sunday.

That is, we're defining what we mean by days being good by saying "Saturday is good, sunday is good, and that's all." Then someone can prove that Sunday is good simply by observing that we said it was when we defined what good_day meant.

The constructor gd_sun is "primitive evidence" — an axiom — justifying the claim that Sunday is good. Similarly, we can define a proposition day_before parameterized by two days, together with axioms stating that Monday comes before Tuesday, Tuesday before Wednesday, and so on.

The axioms that we introduce along with an inductively defined proposition can also involve universal quantifiers. For example, it is well known that every day is a fine day for singing a song:

The line above declares that, if d is a day, then fdfs_any d can be taken as evidence for fine_day_for_singing d. That is, we can construct evidence that d is a fine_day_for_singing by applying the constructor fdfs_any to d. In particular, Wednesday is a fine day for singing.

As always, the first line here can be read "I'm about to show you some evidence for the proposition fine_day_for_singing wednesday, and I want to introduce the name fdfs_wed to refer to that evidence later on." The second line then instructs Coq how to assemble the evidence.

Proof Objects

There's another — more primitive — way to accomplish the same thing: we can use a Definition whose left-hand side is the name we're introducing and whose right-hand side is the evidence itself, rather than a script for how to build it.

The expression fdfs_any wednesday can be thought of as instantiating the parameterized axiom fdfs_any with the specific argument wednesday. Alternatively, we can think of fdfs_any as a primitive "evidence constructor" that, when applied to a particular day, stands as evidence that that day is a fine day for singing; its type, ∀ d:day, fine_day_for_singing d, expresses this functionality, in the same way that the polymorphic type ∀ X, list X in the previous chapter expressed the fact that the constructor nil can be thought of as a function from types to empty lists with elements of that type. Let's take a slightly more interesting example. Let's say that a day of the week is "ok" if either (1) it is a good day or else (2) it falls the day before an ok day.

The first constructor can be read "One way to show that d is an ok day is to present evidence that d is good." The second can be read, "Another way to show that a day d1 is ok is to present evidence that it is the day before some other day d2 together with evidence that d2 is ok." Now suppose that we want to prove that wednesday is ok. There are two ways to do it. First, we have the primitive way, where we simply write down an expression that has the right type — a big nested application of constructors:

Second, we have the machine-assisted way, where we go into Proof mode and Coq guides us through a series of goals and subgoals until it is finally satisfied:

Fundamentally, though, these two ways of making proofs are the same, in the sense that what Coq is actually doing when it's following the commands in a Proof script is literally attempting to construct an expression with the desired type.

These expressions are often called proof objects. Proof objects are the bedrock of Coq. Tactic proofs are essentially programs that instruct Coq how to construct proof objects for us instead of our writing them out explicitly. Here, of course, the proof object is actually shorter than the tactic proof. But the proof objects for more interesting proofs can become quite large and complex — building them by hand would be painful. Moreover, we'll see later on in the course that Coq has a number of automation tactics that can construct quite complex proof objects without our needing to specify every step.

The Curry-Howard Correspondence

The analogy

                 propositions  ~  sets / types
                 proofs        ~  data values 

is called the Curry-Howard correspondence (or Curry-Howard isomorphism). Many wonderful things follow from it. Just as a set can be empty, a singleton, finite, or infinite — it can have zero, one, or many inhabitants — a proposition may be inhabited by zero, one, many, or infinitely many proofs. Each inhabitant of a proposition P is a different way of giving evidence for P. If there are none, then P is not provable. If there are many, then P has many different proofs.

Implication

We've seen that the → operator (implication) builds bigger propositions from smaller ones. What constitutes evidence for propositions built in this way? Consider this statement:

In English: if we have three days, d1 which is before d2 which is before d3, and if we know d3 is ok, then so is d1. It should be easy to see how we'd construct a tactic proof of okd_before2...

Exercise: 1 star, optional (okd_before2_valid)

☐ But what should the corresponding proof object look like? Answer: We've made a notational pun between → as implication and → as the type of functions. If we take this pun seriously, then what we're looking for is an expression with type ∀ d1 d2 d3, ok_day d3 → day_before d2 d1 → day_before d3 d2 → ok_day d1, and so what we want is a function that takes six arguments (three days and three pieces of evidence) and returns a piece of evidence! Here it is:

Exercise: 1 star, optional (okd_before2_valid_defn)

Predict what Coq will print in response to this:

Induction Principles for Inductively Defined Types

Every time we declare a new Inductive datatype, Coq automatically generates an axiom that embodies an induction principle for this type. The induction principle for a type t is called t_ind. Here is the one for natural numbers:

Note that this is exactly the our_nat_induction property from above. The induction tactic is a straightforward wrapper that, at its core, simply performs apply t_ind. To see this more clearly, let's experiment a little with using apply nat_ind directly, instead of the induction tactic, to carry out some proofs. Here, for example, is an alternate proof of a theorem that we saw in the Basics chapter.

This proof is basically the same as the earlier one, but a few minor differences are worth noting. First, in the induction step of the proof (the "S" case), we have to do a little bookkeeping manually (the intros) that induction does automatically. Second, we do not introduce n into the context before applying nat_ind — the conclusion of nat_ind is a quantified formula, and apply needs this conclusion to exactly match the shape of the goal state, including the quantifier. The induction tactic works either with a variable in the context or a quantified variable in the goal. Third, the apply tactic automatically chooses variable names for us (in the second subgoal, here), whereas induction lets us specify (with the as... clause) what names should be used. The automatic choice is actually a little unfortunate, since it re-uses the name n for a variable that is different from the n in the original theorem. This is why the Case annotation is just S — if we tried to write it out in the more explicit form that we've been using for most proofs, we'd have to write n = S n, which doesn't make a lot of sense! All of these conveniences make induction nicer to use in practice than applying induction principles like nat_ind directly. But it is important to realize that, modulo this little bit of bookkeeping, applying nat_ind is what we are really doing.

Exercise: 2 stars (plus_one_r')

Complete this proof without using the induction tactic.

☐ The induction principles that Coq generates for other datatypes defined with Inductive follow a similar pattern. If we define a type t with constructors c1 ... cn, Coq generates a theorem with this shape: The specific shape of each case depends on the arguments to the corresponding constructor. Before trying to write down a general rule, let's look at some more examples. First, an example where the constructors take no arguments:

Exercise: 1 star (rgb)

Write out the induction principle that Coq will generate for the following datatype. Write down your answer on paper, and then compare it with what Coq prints.

☐ Here's another example, this time with one of the constructors taking some arguments.

Exercise: 1 star (natlist1)

Suppose we had written the above definition a little differently:

Now what will the induction principle look like? ☐ From these examples, we can extract this general rule:

• The type declaration gives several constructors; each corresponds to one clause of the induction principle.
• Each constructor c takes argument types a1...an.
• Each ai can be either t (the datatype we are defining) or some other type s.
• The corresponding case of the induction principle says (in English):
  • "for all values x1...xn of types a1...an, if P holds for each of the xs of type t, then P holds for c x1 ... xn".

Exercise: 1 star (ExSet)

Here is an induction principle for an inductively defined set. Give an Inductive definition of ExSet:

☐ What about polymorphic datatypes? The inductive definition of polymorphic lists is very similar to that of natlist. The main difference is that, here, the whole definition is parameterized on a set X: that is, we are defining a family of inductive types list X, one for each X. (Note that, wherever list appears in the body of the declaration, it is always applied to the parameter X.) The induction principle is likewise parameterized on X: Note the wording here (and, accordingly, the form of list_ind): The whole induction principle is parameterized on X. That is, list_ind can be thought of as a polymorphic function that, when applied to a type X, gives us back an induction principle specialized to the type list X.

Exercise: 1 star (tree)

Write out the induction principle that Coq will generate for the following datatype. Compare your answer with what Coq prints.

☐

Exercise: 1 star (mytype)

Find an inductive definition that gives rise to the following induction principle: ☐

Exercise: 1 star, optional (foo)

Find an inductive definition that gives rise to the following induction principle: ☐

Exercise: 1 star, optional (foo')

Consider the following inductive definition:

What induction principle will Coq generate for foo'? Fill in the blanks, then check your answer with Coq.) ☐

Induction Hypotheses

Where does the phrase "induction hypothesis" fit into this picture? The induction principle for numbers is a generic statement that holds for all propositions P (strictly speaking, for all families of propositions P indexed by a number n). Each time we use this principle, we are choosing P to be a particular expression of type nat→Prop. We can make the proof more explicit by giving this expression a name. For example, instead of stating the theorem mult_0_r as "∀ n, n * 0 = 0," we can write it as "∀ n, P_m0r n", where P_m0r is defined as...

... or equivalently...

Now when we do the proof it is easier to see where P_m0r appears.

This extra naming step isn't something that we'll do in normal proofs, but it is useful to do it explicitly for an example or two, because it allows us to see exactly what the induction hypothesis is. If we prove ∀ n, P_m0r n by induction on n (using either induction or apply nat_ind), we see that the first subgoal requires us to prove P_m0r 0 ("P holds for zero"), while the second subgoal requires us to prove ∀ n', P_m0r n' → P_m0r n' (S n') (that is "P holds of S n' if it holds of n'" or, more elegantly, "P is preserved by S"). The induction hypothesis is the premise of this latter implication — the assumption that P holds of n', which we are allowed to use in proving that P holds for S n'.

Evenness Again

Some of the examples in the opening discussion of propositions involved the concept of evenness. We began with a computation evenb n that checks evenness, yielding a boolean. From this, we built a proposition even n (defined in terms of evenb) that asserts that n is even. That is, we defined "n is even" to mean "evenb returns true when applied to n." Another alternative is to define the concept of evenness directly. Instead of going indirectly via the evenb function ("a number is even if a certain computation yields true"), we can say directly what the concept of evenness means in terms of evidence.

This definition says that there are two ways to give evidence that a number m is even. First, 0 is even, and ev_0 is evidence for this. Second, if m = S (S n) for some n and we can give evidence e that n is even, then m is also even, and ev_SS n e is the evidence.

Exercise: 1 star, optional (four_ev)

Give a tactic proof and a proof object showing that four is even.

☐

Exercise: 2 stars (ev_plus4)

Give a tactic proof and a proof object showing that, if n is even, then so is 4+n.

☐

Exercise: 2 stars (double_even)

Construct a tactic proof of the following proposition.

☐

Exercise: 4 stars, optional (double_even_pfobj)

Try to predict what proof object is constructed by the above tactic proof. (Before checking your answer, you'll want to strip out any uses of Case, as these will make the proof object look a bit cluttered.) ☐

Reasoning by Induction Over Evidence

The highly "orthogonal" organization of Coq's design might suggest that, since we use the keyword Induction to define primitive propositions together with their evidence, there must be some sort of induction principles associated with these definitions. Indeed there are, and in this section we'll take a look at how they can be used. To get warmed up, let's look at how the simpler destruct tactic works with inductively defined evidence. Besides constructing evidence of evenness, we can also reason about evidence of evenness. The fact that we introduced ev with an Inductive declaration tells us not only that the constructors ev_0 and ev_SS are ways to build evidence of evenness, but also that these two constructors are the only ways that evidence of evenness can be built. In other words, if someone gives us evidence E justifying the assertion ev n, then we know that E can only have one of two forms: either E is ev_0 (and n is O), or E is ev_SS n' E' (and n is S (S n')) and E' is evidence that n' is even. Thus, it makes sense to use the tactics that we have already seen for inductively defined data to reason instead about inductively defined evidence. For example, here we use a destruct on evidence that n is even in order to show that ev n implies ev (n-2).

Exercise: 1 star (ev_minus2_n)

What happens if we try to destruct on n instead of E? ☐ We can also perform induction on evidence that n is even. Here we use it to show that the old evenb function returns true on n when n is even according to ev.

(Of course, we'd expect that even n → ev n also holds. We'll see how to prove it in the next chapter.)

Exercise: 1 star (ev_even_n)

Could this proof be carried out by induction on n instead of E? ☐ The induction principle for inductively defined propositions does not follow quite the same form as that of inductively defined sets. For now, you can take the intuitive view that induction on evidence ev n is similar to induction on n, but restricts our attention to only those numbers for which evidence ev n could be generated. We'll look at the induction principle of ev in more depth below, to explain what's really going on.

Exercise: 1 star (l_fails)

The following proof attempt will not succeed. Briefly explain why. (* FILL IN HERE *)
☐

Exercise: 2 stars (ev_sum)

Here's another exercise requiring induction.

☐ Here's another situation where we want to analyze evidence for evenness: proving that if n+2 is even, then n is. Our first idea might be to use destruct for this kind of case analysis:

But this doesn't work. For example, in the first sub-goal, we've lost the information that n is 0. The right thing to use here, it turns out, is inversion:

This use of inversion may seem a bit mysterious at first. Until now, we've only used inversion on equality propositions, to utilize injectivity of constructors or to discriminate between different constructors. But we see here that inversion can also be applied to analyzing evidence for inductively defined propositions. Here's how inversion works in general. Suppose the name I refers to an assumption P in the current context, where P has been defined by an Inductive declaration. Then, for each of the constructors of P, inversion I generates a subgoal in which I has been replaced by the exact, specific conditions under which this constructor could have been used to prove P. Some of these subgoals will be self-contradictory; inversion throws these away. The ones that are left represent the cases that must be proved to establish the original goal. In this particular case, the inversion analyzed the construction ev (S (S n)), determined that this could only have been constructed using ev_SS, and generated a new subgoal with the arguments of that constructor as new hypotheses. (It also produced an auxiliary equality, which happens to be useless here.) We'll begin exploring this more general behavior of inversion in what follows.

Exercise: 1 star (inversion_practice)

The inversion tactic can also be used to derive goals by showing the absurdity of a hypothesis.

☐ We can generally use inversion instead of destruct on inductive propositions. This illustrates that in general, we get one case for each possible constructor. Again, we also get some auxiliary equalities that are rewritten in the goal but not in the other hypotheses.

Exercise: 3 stars (ev_ev_even)

Finding the appropriate thing to do induction on is a bit tricky here:

☐

Exercise: 3 stars, optional (ev_plus_plus)

Here's an exercise that just requires applying existing lemmas. No induction or even case analysis is needed, but some of the rewriting may be tedious. You'll want the replace tactic used for plus_swap' in Basics.v

☐

Why Define Propositions Inductively?

We have seen that the proposition "some number is even" can be phrased in two different ways — indirectly, via a testing function evenb, or directly, by inductively describing what constitutes evidence for evenness. These two ways of defining evenness are about equally easy to state and work with. Which we choose is basically a question of taste. However, for many other properties of interest, the direct inductive definition is preferable, since writing a testing function may be awkward or even impossible. For example, consider the property MyProp defined as follows:

• the number 4 has property MyProp
• if n has property MyProp, then so does 4+n
• if 2+n has property MyProp, then so does n
• no other numbers have property MyProp

This is a perfectly sensible definition of a set of numbers, but we cannot translate this definition directly as a Coq Fixpoint (or translate it directly into a recursive function in any other programming language). We might be able to find a clever way of testing this property using a Fixpoint (indeed, it is not too hard to find one in this case), but in general this could require arbitrarily much thinking. In fact, if the property we are interested in is uncomputable, then we cannot define it as a Fixpoint no matter how hard we try, because Coq requires that all Fixpoints correspond to terminating computations. On the other hand, writing an inductive definition of what it means to give evidence for the property MyProp is straightforward:

The first three clauses in the informal definition of MyProp above are reflected in the first three clauses of the inductive definition. The fourth clause is the precise force of the keyword Inductive. As we did with evenness, we can now construct evidence that certain numbers satisfy MyProp.

Exercise: 2 stars (MyProp)

Here are two useful facts about MyProp. The proofs are left to you.

☐ With these, we can show that MyProp holds of all even numbers, and vice versa.

Here's an informal proof of this theorem: Theorem: For any nat n, if ev n then MyProp n. Proof: Suppose n is a nat and E is a derivation of ev n. We must exhibit a derivation of MyProp n. The proof is by induction on E. There are two cases to consider:

• If the last step in E is a use of ev_0, then n is 0. Then we must show that MyProp 0 holds; this is true by lemma MyProp_0.
• If the last step in E is a use of ev_SS, then n = S (S n') for some n', and there is a derivation of ev n'. We must show MyProp (S (S n')), with the induction hypothesis that MyProp n' holds. But by lemma MyProp_plustwo, it's enough to show MyProp n', which is exactly the induction hypothesis. ☐

Exercise: 3 stars (ev_MyProp)

☐

Exercise: 3 stars, optional (ev_MyProp_informal)

Write an informal proof corresponding to your formal proof of ev_MyProp: Theorem: For any nat n, if MyProp n then ev n. Proof: (* FILL IN HERE *)
☐

The Big Picture: Coq's Two Universes

Now that we've touched on several of Coq's basic structures, it may be useful to take a step back and talk a little about how it all fits together. Expressions in Coq live in two distinct universes:

• Type is the universe of computations and data.
• Prop is the universe of logical assertions and evidence.

The two universes have some deep similarities — in each, we can talk about values, inductive definitions, quantification, etc. — but they play quite different roles in defining and reasoning about mathematical structures.

Values

Both universes start with an infinite set of constructors. Constructors have no internal structure: they are just atomic symbols. For example, true, false, O, S, nil, cons, ev_0, ev_SS, ... The simplest values are expressions consisting entirely of constructor applications. Examples include:

• true
• O
• S (S (S O))
• ev_0
• ev_SS (S (S O)) ev_0
• ev_SS (S (S (S (S O)))) (ev_SS (S (S O)) ev_0)

Such expressions can be thought of as trees. Their leaves are nullary constructors (applied to no arguments), and their internal nodes are applications of constructors to one or more values. In the universe Type, we think of values as data. In Prop, we think of values as evidence. Values in Prop are sometimes called derivation trees. Functions are also values — for example:

• fun x => true
• fun b => negb b
• fun n => S (S (S n))
• fun n => fun (P : ev n) => ev_SS (S (S n)) P

Functions that return values in the universe Type represent computations: they take some input values and return an output value computed from the inputs. Functions returning values in Prop are universally quantified evidence: that is, they use their inputs to build evidence for some proposition (whose statement may also involve these inputs).

Inductive Definitions

Inductive declarations give names to subsets of the set of all values. For example, the declaration of the inductive type nat defines a set whose elements are values representing natural numbers. That is, it picks out a subset nat of the set of all values that satisfies the following properties:

• the value O is in this set;
• the set is closed under applications of S (i.e., if a value n is in the set, then S n is too);
• it is the smallest set satisfying these conditions (i.e., the only values in nat are the ones that must be, according to the previous two conditions; there is no other "junk").

Inductively defined sets can themselves appear as arguments to constructors in compound values. Examples:

• nat
• nil nat
• cons nat O (cons nat (S O) (nil nat))

Also, we can write functions that take sets as arguments and return sets as results. For example, list is a function that takes a set X as argument and returns as result the set list X (whose members are lists with elements drawn from X). Similarly, the declaration of the inductive type ev defines a family of propositions whose elements are values representing evidence that numbers are even. That is, for each n, the definition picks out a subset ev n of the set of all values, satisfying the following properties:

• the value ev_0 is in the set ev O;
• the sets are closed under well-typed applications of ev_SS — i.e., if e is in the set ev n, then ev_SS n e is in the set ev (S (S n));
• it is the smallest family of sets satisfying these conditions (i.e., the only values in any set ev n are the ones that must be, according to the previous two conditions; there is no other junk).

Types and Kinds

Informally, a type in Coq is an expression that is used to classify other expressions. For example, bool, nat, list bool, list nat, nat→nat, and so on are all types. The type bool classifies true and false; the type nat classifies O, S O, S (S O), etc.; the type nat→nat classifies function values (like fun n => S n) that yield a number when given a number as input. Type, Prop, and compound expressions built from them (like Type→Type) play a similar classifying role "one level up" — that is, they can be thought of as the types of type (and proposition) expressions. Technically, they are called kinds, to avoid too many uses of the word "type." For example, the expressions nat, nat→nat and list nat all have kind Type, while list itself has kind Type→Type and ev has kind nat→Prop.

Propositions vs. Booleans

Propositions and booleans are superficially similar, but they are really quite different things!

• Booleans are values in the computational world. Every expression of type bool (with no free variables) can be simplified to either true or false.
• Propositions are types in the logical world. They are either provable (i.e., there is some expression that has this type) or not (there is no such expression). It doesn't make sense to say that a proposition is "equivalent to true."
  We sometimes use the words "true" and "false" informally when referring to propositions. Strictly speaking, this is wrong: a proposition is either provable or it is not.

Functions vs. Quantifiers

The types A→B and ∀ x:A, B both describe functions from A to B. The only difference is that, in the second case, the expression B — the type of the result — can mention the argument x by name. For example:

• The function fun x:nat => x + x has type nat→nat — that is, it maps each number n to a number.
• The function fun X:Type => nil (list X) has type ∀ X:Type, list (list X) — that is, it maps each set X to a particular list of lists of Xs. (Of course, nil is usually written as [] instead of nil X.)

In fact, the two ways of writing function types are really the same: In Coq, A→B is actually just an abbreviation for ∀ x:A, B, where x is some variable name not occurring in B. For example, the type of fun x:nat => x + x can be written, if we like, as ∀ x:nat, nat.

Functions vs. Implications

In both Type and Prop, we can write functions that transform values into other values. Also, functions themselves are values; this means we can

• write higher-order functions that take functions as arguments or return functions as results, and
• apply constructors to functions to build complex values containing functions.

A function of type P→Q in Prop is something that takes evidence for P as an argument and yields evidence for Q as its result. Such a function can be regarded as evidence that P implies Q, since, whenever we have evidence that P is true, we can apply the function and get back evidence that Q is true: evidence for an implication is a function on evidence. This is why we use the same notation for functions and logical implications in Coq: they are exactly the same thing!

Informal Proofs

Q: What is the relation between a formal proof of a proposition P and an informal proof of the same proposition P? A: The latter should teach the reader how to produce the former. Q: How much detail is needed? A: There is no single right answer; rather, there is a range of choices. At one end of the spectrum, we can essentially give the reader the whole formal proof (i.e., the informal proof amounts to just transcribing the formal one into words). This gives the reader the ability to reproduce the formal one for themselves, but it doesn't teach them anything. At the other end of the spectrum, we can say "The theorem is true and you can figure out why for yourself if you think about it hard enough." This is also not a good teaching strategy, because usually writing the proof requires some deep insights into the thing we're proving, and most readers will give up before they rediscover all the same insights as we did. In the middle is the golden mean — a proof that includes all of the essential insights (saving the reader the hard part of work that we went through to find the proof in the first place) and clear high-level suggestions for the more routine parts to save the reader from spending too much time reconstructing these parts (e.g., what the IH says and what must be shown in each case of an inductive proof), but not so much detail that the main ideas are obscured. Another key point: if we're talking about a formal proof of a proposition P and an informal proof of P, the proposition P doesn't change. That is, formal and informal proofs are talking about the same world and they must play by the same rules.

Informal Proofs by Induction

Since we've spent much of this chapter looking "under the hood" at formal proofs by induction, now is a good moment to talk a little about informal proofs by induction. In the real world of mathematical communication, written proofs range from extremely longwinded and pedantic to extremely brief and telegraphic. The ideal is somewhere in between, of course, but while you are getting used to the style it is better to start out at the pedantic end. Also, during the learning phase, it is probably helpful to have a clear standard to compare against. With this in mind, we offer two templates below — one for proofs by induction over data (i.e., where the thing we're doing induction on lives in Type) and one for proofs by induction over evidence (i.e., where the inductively defined thing lives in Prop). In the rest of this course, please follow one of the two for all of your inductive proofs.

Induction Over an Inductively Defined Set

Template:

• Theorem: <Universally quantified proposition of the form "For all n:S, P(n)," where S is some inductively defined set.>
  Proof: By induction on n.
  <one case for each constructor c of S...>
  • Suppose n = c a1 ... ak, where <...and here we state the IH for each of the a's that has type S, if any>. We must show <...and here we restate P(c a1 ... ak)>.
    <go on and prove P(n) to finish the case...>
  • <other cases similarly...> ☐

Example:

• Theorem: For all sets X, lists l : list X, and numbers n, if length l = n then index (S n) l = None.
  Proof: By induction on l.
  • Suppose l = []. We must show, for all numbers n, that, if length [] = n, then index (S n) [] = None.
    This follows immediately from the definition of index.
  • Suppose l = x :: l' for some x and l', where length l' = n' implies index (S n') l' = None, for any number n'. We must show, for all n, that, if length (x::l') = n then index (S n) (x::l') = None.
    Let n be a number with length l = n. Since
      length l = length (x::l') = S (length l'),
    it suffices to show that
      index (S (length l')) l' = None.
    But this follows directly from the induction hypothesis, picking n' to be length l'. ☐

Induction Over an Inductively Defined Proposition

Since inductively defined proof objects are often called "derivation trees," this form of proof is also known as induction on derivations. Template:

• Theorem: <Proposition of the form "Q → P," where Q is some inductively defined proposition (more generally, "For all x y z, Q x y z → P x y z")>
  Proof: By induction on a derivation of Q. <Or, more generally, "Suppose we are given x, y, and z. We show that Q x y z implies P x y z, by induction on a derivation of Q x y z"...>
  <one case for each constructor c of Q...>
  • Suppose the final rule used to show Q is c. Then <...and here we state the types of all of the a's together with any equalities that follow from the definition of the constructor and the IH for each of the a's that has type Q, if there are any>. We must show <...and here we restate P>.
    <go on and prove P to finish the case...>
  • <other cases similarly...> ☐

Example

• Theorem: The <= relation is transitive — i.e., for all numbers n, m, and o, if n <= m and m <= o, then n <= o.
  Proof: By induction on a derivation of m <= o.
  • Suppose the final rule used to show m <= o is le_n. Then m = o and the result is immediate.
  • Suppose the final rule used to show m <= o is le_S. Then o = S o' for some o' with m <= o'. By induction hypothesis, n <= o'.
    But then, by le_S, n <= o. ☐

Optional Material

This section offers some additional details on how induction works in Coq. It can safely be skimmed on a first reading. (We recommend skimming rather than skipping over it outright: it answers some questions that occur to many Coq users at some point, so it is useful to have a rough idea of what's here.)

More on the induction Tactic

The induction tactic actually does even more low-level bookkeeping for us than we discussed above. Recall the informal statement of the induction principle for natural numbers:

• If P n is some proposition involving a natural number n, and we want to show that P holds for all numbers n, we can reason like this:
  • show that P O holds
  • show that, if P n' holds, then so does P (S n')
  • conclude that P n holds for all n.

So, when we begin a proof with intros n and then induction n, we are first telling Coq to consider a particular n (by introducing it into the context) and then telling it to prove something about all numbers (by using induction). What Coq actually does in this situation, internally, is to "re-generalize" the variable we perform induction on. For example, in the proof above that plus is associative...

It also works to apply induction to a variable that is quantified in the goal.

Note that induction n leaves m still bound in the goal — i.e., what we are proving inductively is a statement beginning with ∀ m. If we do induction on a variable that is quantified in the goal after some other quantifiers, the induction tactic will automatically introduce the variables bound by these quantifiers into the context.

Exercise: 1 star, optional (plus_explicit_prop)

Rewrite both plus_assoc' and plus_comm' and their proofs in the same style as mult_0_r'' above — that is, for each theorem, give an explicit Definition of the proposition being proved by induction, and state the theorem and proof in terms of this defined proposition.

☐ One more quick digression, for adventurous souls: if we can define parameterized propositions using Definition, then can we also define them using Fixpoint? Of course we can! However, this kind of "recursive parameterization" doesn't correspond to anything very familiar from everyday mathematics. The following exercise gives a slightly contrived example.

Exercise: 4 stars, optional (true_upto_n__true_everywhere)

Define a recursive function true_upto_n__true_everywhere that makes true_upto_n_example work.

☐

Induction Principles in Prop

Earlier, we looked in detail at the induction principles that Coq generates for inductively defined sets. The induction principles for inductively defined propositions like ev are a tiny bit more complicated. As with all induction principles, we want to use the induction principle on ev to prove things by inductively considering the possible shapes that something in ev can have — either it is evidence that 0 is even, or it is evidence that, for some n, S (S n) is even, and it includes evidence that n itself is. Intuitively speaking, however, what we want to prove are not statements about evidence but statements about numbers. So we want an induction principle that lets us prove properties of numbers by induction on evidence. For example, from what we've said so far, you might expect the inductive definition of ev... ...to give rise to an induction principle that looks like this... ... because:

• Since ev is indexed by a number n (every ev object e is a piece of evidence that some particular number n is even), the proposition P is parameterized by both n and e — that is, the induction principle can be used to prove assertions involving both an even number and the evidence that it is even.
• Since there are two ways of giving evidence of evenness (ev has two constructors), applying the induction principle generates two subgoals:
  • We must prove that P holds for O and ev_0.
  • We must prove that, whenever n is an even number and e is evidence of its evenness, if P holds of n and e, then it also holds of S (S n) and ev_SS n e.
• If these subgoals can be proved, then the induction principle tells us that P is true for all even numbers n and evidence e of their evenness.

But this is a little more flexibility than we actually need or want: it is giving us a way to prove logical assertions where the assertion involves properties of some piece of evidence of evenness, while all we really care about is proving properties of numbers that are even — we are interested in assertions about numbers, not about evidence. It would therefore be more convenient to have an induction principle for proving propositions P that are parameterized just by n and whose conclusion establishes P for all even numbers n: For this reason, Coq actually generates the following simplified induction principle for ev:

In particular, Coq has dropped the evidence term e as a parameter of the the proposition P, and consequently has rewritten the assumption ∀ (n:nat) (e:ev n), ... to be ∀ (n:nat), ev n → ...; i.e., we no longer require explicit evidence of the provability of ev n. In English, ev_ind says:

• Suppose, P is a property of natural numbers (that is, P n is a Prop for every n). To show that P n holds whenever n is even, it suffices to show:
  • P holds for 0
  • for any n, if n is even and P holds for n, then P holds for S (S n).

We can apply ev_ind directly instead of using induction, following pretty much the same pattern as above.

Exercise: 3 stars, optional (prop_ind)

Write out the induction principles that Coq will generate for the inductive declarations list and MyProp. Compare your answers against the results Coq prints for the following queries.

☐

Exercise: 3 stars, optional (ev_MyProp')

Prove ev_MyProp again, using apply MyProp_ind instead of the induction tactic.

☐

Exercise: 4 stars, optional (MyProp_pfobj)

Prove MyProp_ev and ev_MyProp again by constructing explicit proof objects by hand (as you did above in ev_plus4, for example).

☐

Exercise: 3 stars, optional (p_provability)

Consider the following inductively defined proposition:

Describe, in English, the conditions under which the proposition p t n is provable. (* FILL IN HERE *)
☐

Additional Exercises

Exercise: 4 stars (palindromes)

A palindrome is a sequence that reads the same backwards as forwards.

• Define an inductive proposition pal on list X that captures what it means to be a palindrome. (Hint: You'll need three cases. Your definition should be based on the structure of the list; just having a single constructor
  c : ∀ l, l = rev l → pal l
  may seem obvious, but will not work very well.)
• Prove that
   ∀ l, pal (l ++ rev l).
• Prove that
   ∀ l, pal l → l = rev l.

☐

Exercise: 5 stars, optional (palindrome_converse)

Using your definition of pal from the previous exercise, prove that

☐

Exercise: 4 stars (subsequence)

A list is a subsequence of another list if all of the elements in the first list occur in the same order in the second list, possibly with some extra elements in between. For example, is a subsequence of each of the lists but it is not a subsequence of any of the lists

• Define an inductive proposition subseq on list nat that captures what it means to be a subsequence. (Hint: You'll need three cases.)
• Prove that subsequence is reflexive, that is, any list is a subsequence of itself.
• Prove that for any lists l1, l2, and l3, if l1 is a subsequence of l2, then l1 is also a subsequence of l2 ++ l3.
• (Optional, harder) Prove that subsequence is transitive — that is, if l1 is a subsequence of l2 and l2 is a subsequence of l3, then l1 is a subsequence of l3. Hint: choose your induction carefully!

☐

Exercise: 2 stars, optional (foo_ind_principle)

Suppose we make the following inductive definition: Fill in the blanks to complete the induction principle that will be generated by Coq. ☐

Exercise: 2 stars, optional (bar_ind_principle)

Consider the following induction principle: Write out the corresponding inductive set definition. ☐

Exercise: 2 stars, optional (no_longer_than_ind)

Given the following inductively defined proposition: write the induction principle generated by Coq. ☐

Exercise: 2 stars, optional (R_provability)

Suppose we give Coq the following definition: Which of the following propositions are provable?

• R 2 [1,0]
• R 1 [1,2,1,0]
• R 6 [3,2,1,0]

☐