# Lambda: Introduction to Lambda Calculus

module plfa.part2.Lambda where

The *lambda-calculus*, first published by the logician Alonzo Church in 1932, is a core calculus with only three syntactic constructs: variables, abstraction, and application. It captures the key concept of *functional abstraction*, which appears in pretty much every programming language, in the form of either functions, procedures, or methods. The *simply-typed lambda calculus* (or STLC) is a variant of the lambda calculus published by Church in 1940. It has the three constructs above for function types, plus whatever else is required for base types. Church had a minimal base type with no operations. We will instead echo Plotkin’s *Programmable Computable Functions* (PCF), and add operations on natural numbers and recursive function definitions.

This chapter formalises the simply-typed lambda calculus, giving its syntax, small-step semantics, and typing rules. The next chapter Properties proves its main properties, including progress and preservation. Following chapters will look at a number of variants of lambda calculus.

Be aware that the approach we take here is *not* our recommended approach to formalisation. Using de Bruijn indices and intrinsically-typed terms, as we will do in Chapter DeBruijn, leads to a more compact formulation. Nonetheless, we begin with named variables and extrinsically-typed terms, partly because names are easier than indices to read, and partly because the development is more traditional.

The development in this chapter was inspired by the corresponding development in Chapter *Stlc* of *Software Foundations* (*Programming Language Foundations*). We differ by representing contexts explicitly (as lists pairing identifiers with types) rather than as partial maps (which take identifiers to types), which corresponds better to our subsequent development of DeBruijn notation. We also differ by taking natural numbers as the base type rather than booleans, allowing more sophisticated examples. In particular, we will be able to show (twice!) that two plus two is four.

## Imports

open import Data.Bool using (Bool; true; false; T; not) open import Data.Empty using (⊥; ⊥-elim) open import Data.List using (List; _∷_; []) open import Data.Nat using (ℕ; zero; suc) open import Data.Product using (∃-syntax; _×_) open import Data.String using (String; _≟_) open import Data.Unit using (tt) open import Relation.Nullary using (Dec; yes; no; ¬_) open import Relation.Nullary.Decidable using (False; toWitnessFalse) open import Relation.Nullary.Negation using (¬?) open import Relation.Binary.PropositionalEquality using (_≡_; _≢_; refl)

## Syntax of terms

Terms have seven constructs. Three are for the core lambda calculus:

- Variables
`` x`

- Abstractions
`ƛ x ⇒ N`

- Applications
`L · M`

Three are for the naturals:

- Zero
``zero`

- Successor
``suc M`

- Case
`case L [zero⇒ M |suc x ⇒ N ]`

And one is for recursion:

- Fixpoint
`μ x ⇒ M`

Abstraction is also called *lambda abstraction*, and is the construct from which the calculus takes its name.

With the exception of variables and fixpoints, each term form either constructs a value of a given type (abstractions yield functions, zero and successor yield natural numbers) or deconstructs it (applications use functions, case terms use naturals). We will see this again when we come to the rules for assigning types to terms, where constructors correspond to introduction rules and deconstructors to eliminators.

Here is the syntax of terms in Backus-Naur Form (BNF):

```
L, M, N ::=
` x | ƛ x ⇒ N | L · M |
`zero | `suc M | case L [zero⇒ M |suc x ⇒ N ] |
μ x ⇒ M
```

And here it is formalised in Agda:Id : Set Id = String infix 5 ƛ_⇒_ infix 5 μ_⇒_ infixl 7 _·_ infix 8 `suc_ infix 9 `_ data Term : Set where `_ : Id → Term ƛ_⇒_ : Id → Term → Term _·_ : Term → Term → Term `zero : Term `suc_ : Term → Term case_[zero⇒_|suc_⇒_] : Term → Term → Id → Term → Term μ_⇒_ : Id → Term → Term

We represent identifiers by strings. We choose precedence so that lambda abstraction and fixpoint bind least tightly, then application, then successor, and tightest of all is the constructor for variables. Case expressions are self-bracketing.

### Example terms

Here are a couple of example terms: the natural number two and a function that adds naturals:two : Term two = `suc `suc `zero plus : Term plus = μ "+" ⇒ ƛ "m" ⇒ ƛ "n" ⇒ case ` "m" [zero⇒ ` "n" |suc "m" ⇒ `suc (` "+" · ` "m" · ` "n") ]

The recursive definition of addition is similar to our original definition of `_+_`

for naturals, as given in Chapter Naturals. Here variable “m” is bound twice, once in a lambda abstraction and once in the successor branch of the case; the first use of “m” refers to the former and the second to the latter. Any use of “m” in the successor branch must refer to the latter binding, and so we say that the latter binding *shadows* the former. Later we will confirm that two plus two is four, in other words that the term

`plus · two · two`

reduces to ``suc `suc `suc `suc `zero`

.

*n*is represented by a function that accepts two arguments and applies the first

*n*times to the second. This is called the

*Church representation*of the naturals. Here are a few example terms: the Church numeral two, a function that adds Church numerals, and a function to compute successor:

twoᶜ : Term twoᶜ = ƛ "s" ⇒ ƛ "z" ⇒ ` "s" · (` "s" · ` "z") plusᶜ : Term plusᶜ = ƛ "m" ⇒ ƛ "n" ⇒ ƛ "s" ⇒ ƛ "z" ⇒ ` "m" · ` "s" · (` "n" · ` "s" · ` "z") sucᶜ : Term sucᶜ = ƛ "n" ⇒ `suc (` "n")

The Church numeral for two takes two arguments `s`

and `z`

and applies `s`

twice to `z`

. Addition takes two numerals `m`

and `n`

, a function `s`

and an argument `z`

, and it uses `m`

to apply `s`

to the result of using `n`

to apply `s`

to `z`

; hence `s`

is applied `m`

plus `n`

times to `z`

, yielding the Church numeral for the sum of `m`

and `n`

. For convenience, we define a function that computes successor. To convert a Church numeral to the corresponding natural, we apply it to the `sucᶜ`

function and the natural number zero. Again, later we will confirm that two plus two is four, in other words that the term

`plusᶜ · twoᶜ · twoᶜ · sucᶜ · `zero`

reduces to ``suc `suc `suc `suc `zero`

.

#### Exercise `mul`

(recommended)

Write out the definition of a lambda term that multiplies two natural numbers. Your definition may use `plus`

as defined earlier.

-- Your code goes here

#### Exercise `mulᶜ`

(practice)

Write out the definition of a lambda term that multiplies two natural numbers represented as Church numerals. Your definition may use `plusᶜ`

as defined earlier (or may not — there are nice definitions both ways).

-- Your code goes here

#### Exercise `primed`

(stretch)

Some people find it annoying to write `` "x"`

instead of `x`

. We can make examples with lambda terms slightly easier to write by adding the following definitions:var? : (t : Term) → Bool var? (` _) = true var? _ = false ƛ′_⇒_ : (t : Term) → {_ : T (var? t)} → Term → Term ƛ′_⇒_ (` x) N = ƛ x ⇒ N case′_[zero⇒_|suc_⇒_] : Term → Term → (t : Term) → {_ : T (var? t)} → Term → Term case′ L [zero⇒ M |suc (` x) ⇒ N ] = case L [zero⇒ M |suc x ⇒ N ] μ′_⇒_ : (t : Term) → {_ : T (var? t)} → Term → Term μ′ (` x) ⇒ N = μ x ⇒ N

Recall that `T`

is a function that maps from the computation world to the evidence world, as defined in Chapter Decidable. We ensure to use the primed functions only when the respective term argument is a variable, which we do by providing implicit evidence. For example, if we tried to define an abstraction term that binds anything but a variable:

```
_ : Term
_ = ƛ′ two ⇒ two
```

Agda would complain it cannot find a value of the bottom type for the implicit argument. Note the implicit argument’s type reduces to `⊥`

when term `t`

is anything but a variable.

`plus`

can now be written as follows:plus′ : Term plus′ = μ′ + ⇒ ƛ′ m ⇒ ƛ′ n ⇒ case′ m [zero⇒ n |suc m ⇒ `suc (+ · m · n) ] where + = ` "+" m = ` "m" n = ` "n"

Write out the definition of multiplication in the same style.

### Formal vs informal

In informal presentation of formal semantics, one uses choice of variable name to disambiguate and writes `x`

rather than `` x`

for a term that is a variable. Agda requires we distinguish.

Similarly, informal presentation often use the same notation for function types, lambda abstraction, and function application in both the *object language* (the language one is describing) and the *meta-language* (the language in which the description is written), trusting readers can use context to distinguish the two. Agda is not quite so forgiving, so here we use `ƛ x ⇒ N`

and `L · M`

for the object language, as compared to `λ x → N`

and `L M`

in our meta-language, Agda.

### Bound and free variables

In an abstraction `ƛ x ⇒ N`

we call `x`

the *bound* variable and `N`

the *body* of the abstraction. A central feature of lambda calculus is that consistent renaming of bound variables leaves the meaning of a term unchanged. Thus the five terms

`ƛ "s" ⇒ ƛ "z" ⇒ ` "s" · (` "s" · ` "z")`

`ƛ "f" ⇒ ƛ "x" ⇒ ` "f" · (` "f" · ` "x")`

`ƛ "sam" ⇒ ƛ "zelda" ⇒ ` "sam" · (` "sam" · ` "zelda")`

`ƛ "z" ⇒ ƛ "s" ⇒ ` "z" · (` "z" · ` "s")`

`ƛ "😇" ⇒ ƛ "😈" ⇒ ` "😇" · (` "😇" · ` "😈" )`

are all considered equivalent. Following the convention introduced by Haskell Curry, who used the Greek letter `α`

(*alpha*) to label such rules, this equivalence relation is called *alpha renaming*.

As we descend from a term into its subterms, variables that are bound may become free. Consider the following terms:

`ƛ "s" ⇒ ƛ "z" ⇒ ` "s" · (` "s" · ` "z")`

has both`s`

and`z`

as bound variables.`ƛ "z" ⇒ ` "s" · (` "s" · ` "z")`

has`z`

bound and`s`

free.`` "s" · (` "s" · ` "z")`

has both`s`

and`z`

as free variables.

We say that a term with no free variables is *closed*; otherwise it is *open*. Of the three terms above, the first is closed and the other two are open. We will focus on reduction of closed terms.

Different occurrences of a variable may be bound and free. In the term

`(ƛ "x" ⇒ ` "x") · ` "x"`

the inner occurrence of `x`

is bound while the outer occurrence is free. By alpha renaming, the term above is equivalent to

`(ƛ "y" ⇒ ` "y") · ` "x"`

in which `y`

is bound and `x`

is free. A common convention, called the *Barendregt convention*, is to use alpha renaming to ensure that the bound variables in a term are distinct from the free variables, which can avoid confusions that may arise if bound and free variables have the same names.

Case and recursion also introduce bound variables, which are also subject to alpha renaming. In the term

```
μ "+" ⇒ ƛ "m" ⇒ ƛ "n" ⇒
case ` "m"
[zero⇒ ` "n"
|suc "m" ⇒ `suc (` "+" · ` "m" · ` "n") ]
```

notice that there are two binding occurrences of `m`

, one in the first line and one in the last line. It is equivalent to the following term,

```
μ "plus" ⇒ ƛ "x" ⇒ ƛ "y" ⇒
case ` "x"
[zero⇒ ` "y"
|suc "x′" ⇒ `suc (` "plus" · ` "x′" · ` "y") ]
```

where the two binding occurrences corresponding to `m`

now have distinct names, `x`

and `x′`

.

## Values

A *value* is a term that corresponds to an answer. Thus, ``suc `suc `suc `suc `zero`

is a value, while `plus · two · two`

is not. Following convention, we treat all function abstractions as values; thus, `plus`

by itself is considered a value.

The predicate `Value M`

holds if term `M`

is a value:

data Value : Term → Set where V-ƛ : ∀ {x N} --------------- → Value (ƛ x ⇒ N) V-zero : ----------- Value `zero V-suc : ∀ {V} → Value V -------------- → Value (`suc V)

In what follows, we let `V`

and `W`

range over values.

### Formal vs informal

In informal presentations of formal semantics, using `V`

as the name of a metavariable is sufficient to indicate that it is a value. In Agda, we must explicitly invoke the `Value`

predicate.

### Other approaches

An alternative is not to focus on closed terms, to treat variables as values, and to treat `ƛ x ⇒ N`

as a value only if `N`

is a value. Indeed, this is how Agda normalises terms. We consider this approach in Chapter Untyped.

## Substitution

The heart of lambda calculus is the operation of substituting one term for a variable in another term. Substitution plays a key role in defining the operational semantics of function application. For instance, we have

```
(ƛ "s" ⇒ ƛ "z" ⇒ ` "s" · (` "s" · ` "z")) · sucᶜ · `zero
—→
(ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · `zero
—→
sucᶜ · (sucᶜ · `zero)
```

where we substitute `sucᶜ`

for `` "s"`

and ``zero`

for `` "z"`

in the body of the function abstraction.

We write substitution as `N [ x := V ]`

, meaning “substitute term `V`

for free occurrences of variable `x`

in term `N`

”, or, more compactly, “substitute `V`

for `x`

in `N`

”, or equivalently, “in `N`

replace `x`

by `V`

”. Substitution works if `V`

is any closed term; it need not be a value, but we use `V`

since in fact we usually substitute values.

Here are some examples:

`(ƛ "z" ⇒ ` "s" · (` "s" · ` "z")) [ "s" := sucᶜ ]`

yields`ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")`

.`(sucᶜ · (sucᶜ · ` "z")) [ "z" := `zero ]`

yields`sucᶜ · (sucᶜ · `zero)`

.`(ƛ "x" ⇒ ` "y") [ "y" := `zero ]`

yields`ƛ "x" ⇒ `zero`

.`(ƛ "x" ⇒ ` "x") [ "x" := `zero ]`

yields`ƛ "x" ⇒ ` "x"`

.`(ƛ "y" ⇒ ` "y") [ "x" := `zero ]`

yields`ƛ "y" ⇒ ` "y"`

.

In the last but one example, substituting ``zero`

for `x`

in `ƛ "x" ⇒ ` "x"`

does *not* yield `ƛ "x" ⇒ `zero`

, since `x`

is bound in the lambda abstraction. The choice of bound names is irrelevant: both `ƛ "x" ⇒ ` "x"`

and `ƛ "y" ⇒ ` "y"`

stand for the identity function. One way to think of this is that `x`

within the body of the abstraction stands for a *different* variable than `x`

outside the abstraction, they just happen to have the same name.

We will give a definition of substitution that is only valid when the term substituted for the variable is closed. This is because substitution by terms that are *not* closed may require renaming of bound variables. For example:

`(ƛ "x" ⇒ ` "x" · ` "y") [ "y" := ` "x" · `zero]`

should not yield`(ƛ "x" ⇒ ` "x" · (` "x" · `zero))`

.

Instead, we should rename the bound variable to avoid capture:

`(ƛ "x" ⇒ ` "x" · ` "y") [ "y" := ` "x" · `zero ]`

should yield`ƛ "x′" ⇒ ` "x′" · (` "x" · `zero)`

.

Here `x′`

is a fresh variable distinct from `x`

. Formal definition of substitution with suitable renaming is considerably more complex, so we avoid it by restricting to substitution by closed terms, which will be adequate for our purposes.

Here is the formal definition of substitution by closed terms in Agda:

infix 9 _[_:=_] _[_:=_] : Term → Id → Term → Term (` x) [ y := V ] with x ≟ y ... | yes _ = V ... | no _ = ` x (ƛ x ⇒ N) [ y := V ] with x ≟ y ... | yes _ = ƛ x ⇒ N ... | no _ = ƛ x ⇒ N [ y := V ] (L · M) [ y := V ] = L [ y := V ] · M [ y := V ] (`zero) [ y := V ] = `zero (`suc M) [ y := V ] = `suc M [ y := V ] (case L [zero⇒ M |suc x ⇒ N ]) [ y := V ] with x ≟ y ... | yes _ = case L [ y := V ] [zero⇒ M [ y := V ] |suc x ⇒ N ] ... | no _ = case L [ y := V ] [zero⇒ M [ y := V ] |suc x ⇒ N [ y := V ] ] (μ x ⇒ N) [ y := V ] with x ≟ y ... | yes _ = μ x ⇒ N ... | no _ = μ x ⇒ N [ y := V ]

Let’s unpack the first three cases:

For variables, we compare

`y`

, the substituted variable, with`x`

, the variable in the term. If they are the same, we yield`V`

, otherwise we yield`x`

unchanged.For abstractions, we compare

`y`

, the substituted variable, with`x`

, the variable bound in the abstraction. If they are the same, we yield the abstraction unchanged, otherwise we substitute inside the body.For application, we recursively substitute in the function and the argument.

Case expressions and recursion also have bound variables that are treated similarly to those in lambda abstractions. Otherwise we simply push substitution recursively into the subterms.

### Examples

Here is confirmation that the examples above are correct:

_ : (ƛ "z" ⇒ ` "s" · (` "s" · ` "z")) [ "s" := sucᶜ ] ≡ ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z") _ = refl _ : (sucᶜ · (sucᶜ · ` "z")) [ "z" := `zero ] ≡ sucᶜ · (sucᶜ · `zero) _ = refl _ : (ƛ "x" ⇒ ` "y") [ "y" := `zero ] ≡ ƛ "x" ⇒ `zero _ = refl _ : (ƛ "x" ⇒ ` "x") [ "x" := `zero ] ≡ ƛ "x" ⇒ ` "x" _ = refl _ : (ƛ "y" ⇒ ` "y") [ "x" := `zero ] ≡ ƛ "y" ⇒ ` "y" _ = refl

#### Quiz

What is the result of the following substitution?

`(ƛ "y" ⇒ ` "x" · (ƛ "x" ⇒ ` "x")) [ "x" := `zero ]`

`(ƛ "y" ⇒ ` "x" · (ƛ "x" ⇒ ` "x"))`

`(ƛ "y" ⇒ ` "x" · (ƛ "x" ⇒ `zero))`

`(ƛ "y" ⇒ `zero · (ƛ "x" ⇒ ` "x"))`

`(ƛ "y" ⇒ `zero · (ƛ "x" ⇒ `zero))`

#### Exercise `_[_:=_]′`

(stretch)

The definition of substitution above has three clauses (`ƛ`

, `case`

, and `μ`

) that invoke a `with`

clause to deal with bound variables. Rewrite the definition to factor the common part of these three clauses into a single function, defined by mutual recursion with substitution.

-- Your code goes here

## Reduction

We give the reduction rules for call-by-value lambda calculus. To reduce an application, first we reduce the left-hand side until it becomes a value (which must be an abstraction); then we reduce the right-hand side until it becomes a value; and finally we substitute the argument for the variable in the abstraction.

In an informal presentation of the operational semantics, the rules for reduction of applications are written as follows:

```
L —→ L′
--------------- ξ-·₁
L · M —→ L′ · M
M —→ M′
--------------- ξ-·₂
V · M —→ V · M′
----------------------------- β-ƛ
(ƛ x ⇒ N) · V —→ N [ x := V ]
```

The Agda version of the rules below will be similar, except that universal quantifications are made explicit, and so are the predicates that indicate which terms are values.

The rules break into two sorts. Compatibility rules direct us to reduce some part of a term. We give them names starting with the Greek letter `ξ`

(*xi*). Once a term is sufficiently reduced, it will consist of a constructor and a deconstructor, in our case `ƛ`

and `·`

, which reduces directly. We give them names starting with the Greek letter `β`

(*beta*) and such rules are traditionally called *beta rules*.

A bit of terminology: A term that matches the left-hand side of a reduction rule is called a *redex*. In the redex `(ƛ x ⇒ N) · V`

, we may refer to `x`

as the *formal parameter* of the function, and `V`

as the *actual parameter* of the function application. Beta reduction replaces the formal parameter by the actual parameter.

If a term is a value, then no reduction applies; conversely, if a reduction applies to a term then it is not a value. We will show in the next chapter that this exhausts the possibilities: every well-typed term either reduces or is a value.

For numbers, zero does not reduce and successor reduces the subterm. A case expression reduces its argument to a number, and then chooses the zero or successor branch as appropriate. A fixpoint replaces the bound variable by the entire fixpoint term; this is the one case where we substitute by a term that is not a value.

Here are the rules formalised in Agda:

infix 4 _—→_ data _—→_ : Term → Term → Set where ξ-·₁ : ∀ {L L′ M} → L —→ L′ ----------------- → L · M —→ L′ · M ξ-·₂ : ∀ {V M M′} → Value V → M —→ M′ ----------------- → V · M —→ V · M′ β-ƛ : ∀ {x N V} → Value V ------------------------------ → (ƛ x ⇒ N) · V —→ N [ x := V ] ξ-suc : ∀ {M M′} → M —→ M′ ------------------ → `suc M —→ `suc M′ ξ-case : ∀ {x L L′ M N} → L —→ L′ ----------------------------------------------------------------- → case L [zero⇒ M |suc x ⇒ N ] —→ case L′ [zero⇒ M |suc x ⇒ N ] β-zero : ∀ {x M N} ---------------------------------------- → case `zero [zero⇒ M |suc x ⇒ N ] —→ M β-suc : ∀ {x V M N} → Value V --------------------------------------------------- → case `suc V [zero⇒ M |suc x ⇒ N ] —→ N [ x := V ] β-μ : ∀ {x M} ------------------------------ → μ x ⇒ M —→ M [ x := μ x ⇒ M ]

The reduction rules are carefully designed to ensure that subterms of a term are reduced to values before the whole term is reduced. This is referred to as *call-by-value* reduction.

Further, we have arranged that subterms are reduced in a left-to-right order. This means that reduction is *deterministic*: for any term, there is at most one other term to which it reduces. Put another way, our reduction relation `—→`

is in fact a function.

This style of explaining the meaning of terms is called a *small-step operational semantics*. If `M —→ N`

, we say that term `M`

*reduces* to term `N`

, or equivalently, term `M`

*steps* to term `N`

. Each compatibility rule has another reduction rule in its premise; so a step always consists of a beta rule, possibly adjusted by zero or more compatibility rules.

#### Quiz

What does the following term step to?

`(ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x") —→ ???`

`(ƛ "x" ⇒ ` "x")`

`(ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x")`

`(ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x")`

What does the following term step to?

`(ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x") —→ ???`

`(ƛ "x" ⇒ ` "x")`

`(ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x")`

`(ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x") · (ƛ "x" ⇒ ` "x")`

What does the following term step to? (Where `twoᶜ`

and `sucᶜ`

are as defined above.)

`twoᶜ · sucᶜ · `zero —→ ???`

`sucᶜ · (sucᶜ · `zero)`

`(ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · `zero`

``zero`

## Reflexive and transitive closure

A single step is only part of the story. In general, we wish to repeatedly step a closed term until it reduces to a value. We do this by defining the reflexive and transitive closure `—↠`

of the step relation `—→`

.

infix 2 _—↠_ infix 1 begin_ infixr 2 _—→⟨_⟩_ infix 3 _∎ data _—↠_ : Term → Term → Set where _∎ : ∀ M --------- → M —↠ M step—→ : ∀ L {M N} → M —↠ N → L —→ M --------- → L —↠ N pattern _—→⟨_⟩_ L L—→M M—↠N = step—→ L M—↠N L—→M begin_ : ∀ {M N} → M —↠ N ------ → M —↠ N begin M—↠N = M—↠N

We can read this as follows:

From term

`M`

, we can take no steps, giving a step of type`M —↠ M`

. It is written`M ∎`

.From term

`L`

we can take a single step of type`L —→ M`

followed by zero or more steps of type`M —↠ N`

, giving a step of type`L —↠ N`

. It is written`L —→⟨ L—→M ⟩ M—↠N`

, where`L—→M`

and`M—↠N`

are steps of the appropriate type.

The notation is chosen to allow us to lay out example reductions in an appealing way, as we will see in the next section.

Recall that in Chapter (Equality)[Equality] we defined chains of equalities using `step-≡`

with a syntax declaration to reverse the order of the arguments, here we similarly introduce `step—→`

with a pattern declaration to reverse the order of the arguments. As before, this happens to allow Agda to perform type inference more efficiently. We will need some long chains of reductions below, so efficiency can be important.

`—→`

and is reflexive and transitive. We do so as follows:data _—↠′_ : Term → Term → Set where step′ : ∀ {M N} → M —→ N ------- → M —↠′ N refl′ : ∀ {M} ------- → M —↠′ M trans′ : ∀ {L M N} → L —↠′ M → M —↠′ N ------- → L —↠′ N

The three constructors specify, respectively, that `—↠′`

includes `—→`

and is reflexive and transitive. A good exercise is to show that the two definitions are equivalent (indeed, one embeds in the other).

#### Exercise `—↠≲—↠′`

(practice)

Show that the first notion of reflexive and transitive closure above embeds into the second. Why are they not isomorphic?

-- Your code goes here

## Confluence

One important property a reduction relation might satisfy is to be *confluent*. If term `L`

reduces to two other terms, `M`

and `N`

, then both of these reduce to a common term `P`

. It can be illustrated as follows:

```
L
/ \
/ \
/ \
M N
\ /
\ /
\ /
P
```

Here `L`

, `M`

, `N`

are universally quantified while `P`

is existentially quantified. If each line stands for zero or more reduction steps, this is called confluence, while if the top two lines stand for a single reduction step and the bottom two stand for zero or more reduction steps it is called the diamond property. In symbols:

postulate confluence : ∀ {L M N} → ((L —↠ M) × (L —↠ N)) -------------------- → ∃[ P ] ((M —↠ P) × (N —↠ P)) diamond : ∀ {L M N} → ((L —→ M) × (L —→ N)) -------------------- → ∃[ P ] ((M —↠ P) × (N —↠ P))

The reduction system studied in this chapter is deterministic. In symbols:

postulate deterministic : ∀ {L M N} → L —→ M → L —→ N ------ → M ≡ N

It is easy to show that every deterministic relation satisfies the diamond and confluence properties. Hence, all the reduction systems studied in this text are trivially confluent.

## Examples

We start with a simple example. The Church numeral two applied to the successor function and zero yields the natural number two:_ : twoᶜ · sucᶜ · `zero —↠ `suc `suc `zero _ = begin twoᶜ · sucᶜ · `zero —→⟨ ξ-·₁ (β-ƛ V-ƛ) ⟩ (ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · `zero —→⟨ β-ƛ V-zero ⟩ sucᶜ · (sucᶜ · `zero) —→⟨ ξ-·₂ V-ƛ (β-ƛ V-zero) ⟩ sucᶜ · `suc `zero —→⟨ β-ƛ (V-suc V-zero) ⟩ `suc (`suc `zero) ∎Here is a sample reduction demonstrating that two plus two is four:

_ : plus · two · two —↠ `suc `suc `suc `suc `zero _ = begin plus · two · two —→⟨ ξ-·₁ (ξ-·₁ β-μ) ⟩ (ƛ "m" ⇒ ƛ "n" ⇒ case ` "m" [zero⇒ ` "n" |suc "m" ⇒ `suc (plus · ` "m" · ` "n") ]) · two · two —→⟨ ξ-·₁ (β-ƛ (V-suc (V-suc V-zero))) ⟩ (ƛ "n" ⇒ case two [zero⇒ ` "n" |suc "m" ⇒ `suc (plus · ` "m" · ` "n") ]) · two —→⟨ β-ƛ (V-suc (V-suc V-zero)) ⟩ case two [zero⇒ two |suc "m" ⇒ `suc (plus · ` "m" · two) ] —→⟨ β-suc (V-suc V-zero) ⟩ `suc (plus · `suc `zero · two) —→⟨ ξ-suc (ξ-·₁ (ξ-·₁ β-μ)) ⟩ `suc ((ƛ "m" ⇒ ƛ "n" ⇒ case ` "m" [zero⇒ ` "n" |suc "m" ⇒ `suc (plus · ` "m" · ` "n") ]) · `suc `zero · two) —→⟨ ξ-suc (ξ-·₁ (β-ƛ (V-suc V-zero))) ⟩ `suc ((ƛ "n" ⇒ case `suc `zero [zero⇒ ` "n" |suc "m" ⇒ `suc (plus · ` "m" · ` "n") ]) · two) —→⟨ ξ-suc (β-ƛ (V-suc (V-suc V-zero))) ⟩ `suc (case `suc `zero [zero⇒ two |suc "m" ⇒ `suc (plus · ` "m" · two) ]) —→⟨ ξ-suc (β-suc V-zero) ⟩ `suc `suc (plus · `zero · two) —→⟨ ξ-suc (ξ-suc (ξ-·₁ (ξ-·₁ β-μ))) ⟩ `suc `suc ((ƛ "m" ⇒ ƛ "n" ⇒ case ` "m" [zero⇒ ` "n" |suc "m" ⇒ `suc (plus · ` "m" · ` "n") ]) · `zero · two) —→⟨ ξ-suc (ξ-suc (ξ-·₁ (β-ƛ V-zero))) ⟩ `suc `suc ((ƛ "n" ⇒ case `zero [zero⇒ ` "n" |suc "m" ⇒ `suc (plus · ` "m" · ` "n") ]) · two) —→⟨ ξ-suc (ξ-suc (β-ƛ (V-suc (V-suc V-zero)))) ⟩ `suc `suc (case `zero [zero⇒ two |suc "m" ⇒ `suc (plus · ` "m" · two) ]) —→⟨ ξ-suc (ξ-suc β-zero) ⟩ `suc (`suc (`suc (`suc `zero))) ∎And here is a similar sample reduction for Church numerals:

_ : plusᶜ · twoᶜ · twoᶜ · sucᶜ · `zero —↠ `suc `suc `suc `suc `zero _ = begin (ƛ "m" ⇒ ƛ "n" ⇒ ƛ "s" ⇒ ƛ "z" ⇒ ` "m" · ` "s" · (` "n" · ` "s" · ` "z")) · twoᶜ · twoᶜ · sucᶜ · `zero —→⟨ ξ-·₁ (ξ-·₁ (ξ-·₁ (β-ƛ V-ƛ))) ⟩ (ƛ "n" ⇒ ƛ "s" ⇒ ƛ "z" ⇒ twoᶜ · ` "s" · (` "n" · ` "s" · ` "z")) · twoᶜ · sucᶜ · `zero —→⟨ ξ-·₁ (ξ-·₁ (β-ƛ V-ƛ)) ⟩ (ƛ "s" ⇒ ƛ "z" ⇒ twoᶜ · ` "s" · (twoᶜ · ` "s" · ` "z")) · sucᶜ · `zero —→⟨ ξ-·₁ (β-ƛ V-ƛ) ⟩ (ƛ "z" ⇒ twoᶜ · sucᶜ · (twoᶜ · sucᶜ · ` "z")) · `zero —→⟨ β-ƛ V-zero ⟩ twoᶜ · sucᶜ · (twoᶜ · sucᶜ · `zero) —→⟨ ξ-·₁ (β-ƛ V-ƛ) ⟩ (ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · (twoᶜ · sucᶜ · `zero) —→⟨ ξ-·₂ V-ƛ (ξ-·₁ (β-ƛ V-ƛ)) ⟩ (ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · ((ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · `zero) —→⟨ ξ-·₂ V-ƛ (β-ƛ V-zero) ⟩ (ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · (sucᶜ · (sucᶜ · `zero)) —→⟨ ξ-·₂ V-ƛ (ξ-·₂ V-ƛ (β-ƛ V-zero)) ⟩ (ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · (sucᶜ · (`suc `zero)) —→⟨ ξ-·₂ V-ƛ (β-ƛ (V-suc V-zero)) ⟩ (ƛ "z" ⇒ sucᶜ · (sucᶜ · ` "z")) · (`suc `suc `zero) —→⟨ β-ƛ (V-suc (V-suc V-zero)) ⟩ sucᶜ · (sucᶜ · `suc `suc `zero) —→⟨ ξ-·₂ V-ƛ (β-ƛ (V-suc (V-suc V-zero))) ⟩ sucᶜ · (`suc `suc `suc `zero) —→⟨ β-ƛ (V-suc (V-suc (V-suc V-zero))) ⟩ `suc (`suc (`suc (`suc `zero))) ∎

In the next chapter, we will see how to compute such reduction sequences.

#### Exercise `plus-example`

(practice)

Write out the reduction sequence demonstrating that one plus one is two.

-- Your code goes here

## Syntax of types

We have just two types:

- Functions,
`A ⇒ B`

- Naturals,
``ℕ`

As before, to avoid overlap we use variants of the names used by Agda.

Here is the syntax of types in BNF:

`A, B, C ::= A ⇒ B | `ℕ`

And here it is formalised in Agda:

infixr 7 _⇒_ data Type : Set where _⇒_ : Type → Type → Type `ℕ : Type

### Precedence

As in Agda, functions of two or more arguments are represented via currying. This is made more convenient by declaring `_⇒_`

to associate to the right and `_·_`

to associate to the left. Thus:

`(`ℕ ⇒ `ℕ) ⇒ `ℕ ⇒ `ℕ`

stands for`((`ℕ ⇒ `ℕ) ⇒ (`ℕ ⇒ `ℕ))`

.`plus · two · two`

stands for`(plus · two) · two`

.

### Quiz

What is the type of the following term?

`ƛ "s" ⇒ ` "s" · (` "s" · `zero)`

`(`ℕ ⇒ `ℕ) ⇒ (`ℕ ⇒ `ℕ)`

`(`ℕ ⇒ `ℕ) ⇒ `ℕ`

``ℕ ⇒ (`ℕ ⇒ `ℕ)`

``ℕ ⇒ `ℕ ⇒ `ℕ`

``ℕ ⇒ `ℕ`

``ℕ`

Give more than one answer if appropriate.

What is the type of the following term?

`(ƛ "s" ⇒ ` "s" · (` "s" · `zero)) · sucᶜ`

`(`ℕ ⇒ `ℕ) ⇒ (`ℕ ⇒ `ℕ)`

`(`ℕ ⇒ `ℕ) ⇒ `ℕ`

``ℕ ⇒ (`ℕ ⇒ `ℕ)`

``ℕ ⇒ `ℕ ⇒ `ℕ`

``ℕ ⇒ `ℕ`

``ℕ`

Give more than one answer if appropriate.

## Typing

### Contexts

While reduction considers only closed terms, typing must consider terms with free variables. To type a term, we must first type its subterms, and in particular in the body of an abstraction its bound variable may appear free.

A *context* associates variables with types. We let `Γ`

and `Δ`

range over contexts. We write `∅`

for the empty context, and `Γ , x ⦂ A`

for the context that extends `Γ`

by associating variable `x`

with type `A`

. For example,

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ`

is the context that associates variable `"s"`

with type ``ℕ ⇒ `ℕ`

, and variable `"z"`

with type ``ℕ`

.

Contexts are formalised as follows:

infixl 5 _,_⦂_ data Context : Set where ∅ : Context _,_⦂_ : Context → Id → Type → Context

#### Exercise `Context-≃`

(practice)

Show that `Context`

is isomorphic to `List (Id × Type)`

. For instance, the isomorphism relates the context

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ`

to the list

`[ ⟨ "z" , `ℕ ⟩ , ⟨ "s" , `ℕ ⇒ `ℕ ⟩ ]`

-- Your code goes here

### Lookup judgment

We have two forms of *judgment*. The first is written

`Γ ∋ x ⦂ A`

and indicates in context `Γ`

that variable `x`

has type `A`

. It is called *lookup*. For example,

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ ∋ "z" ⦂ `ℕ`

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ ∋ "s" ⦂ `ℕ ⇒ `ℕ`

give us the types associated with variables `"z"`

and `"s"`

, respectively. The symbol `∋`

(pronounced “ni”, for “in” backwards) is chosen because checking that `Γ ∋ x ⦂ A`

is analogous to checking whether `x ⦂ A`

appears in a list corresponding to `Γ`

.

If two variables in a context have the same name, then lookup should return the most recently bound variable, which *shadows* the other variables. For example,

`∅ , "x" ⦂ `ℕ ⇒ `ℕ , "x" ⦂ `ℕ ∋ "x" ⦂ `ℕ`

.

Here `"x" ⦂ `ℕ ⇒ `ℕ`

is shadowed by `"x" ⦂ `ℕ`

.

infix 4 _∋_⦂_ data _∋_⦂_ : Context → Id → Type → Set where Z : ∀ {Γ x A} ------------------ → Γ , x ⦂ A ∋ x ⦂ A S : ∀ {Γ x y A B} → x ≢ y → Γ ∋ x ⦂ A ------------------ → Γ , y ⦂ B ∋ x ⦂ A

The constructors `Z`

and `S`

correspond roughly to the constructors `here`

and `there`

for the element-of relation `_∈_`

on lists. Constructor `S`

takes an additional parameter, which ensures that when we look up a variable that it is not *shadowed* by another variable with the same name to its left in the list.

It can be rather tedious to use the `S`

constructor, as you have to provide proofs that `x ≢ y`

each time. For example:

_ : ∅ , "x" ⦂ `ℕ ⇒ `ℕ , "y" ⦂ `ℕ , "z" ⦂ `ℕ ∋ "x" ⦂ `ℕ ⇒ `ℕ _ = S (λ()) (S (λ()) Z)

Instead, we’ll use a “smart constructor”, which uses proof by reflection to check the inequality while type checking:

S′ : ∀ {Γ x y A B} → {x≢y : False (x ≟ y)} → Γ ∋ x ⦂ A ------------------ → Γ , y ⦂ B ∋ x ⦂ A S′ {x≢y = x≢y} x = S (toWitnessFalse x≢y) x

### Typing judgment

The second judgment is written

`Γ ⊢ M ⦂ A`

and indicates in context `Γ`

that term `M`

has type `A`

. Context `Γ`

provides types for all the free variables in `M`

. For example:

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ ⊢ ` "z" ⦂ `ℕ`

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ ⊢ ` "s" ⦂ `ℕ ⇒ `ℕ`

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ ⊢ ` "s" · ` "z" ⦂ `ℕ`

`∅ , "s" ⦂ `ℕ ⇒ `ℕ , "z" ⦂ `ℕ ⊢ ` "s" · (` "s" · ` "z") ⦂ `ℕ`

`∅ , "s" ⦂ `ℕ ⇒ `ℕ ⊢ ƛ "z" ⇒ ` "s" · (` "s" · ` "z") ⦂ `ℕ ⇒ `ℕ`

`∅ ⊢ ƛ "s" ⇒ ƛ "z" ⇒ ` "s" · (` "s" · ` "z") ⦂ (`ℕ ⇒ `ℕ) ⇒ `ℕ ⇒ `ℕ`

infix 4 _⊢_⦂_ data _⊢_⦂_ : Context → Term → Type → Set where -- Axiom ⊢` : ∀ {Γ x A} → Γ ∋ x ⦂ A ----------- → Γ ⊢ ` x ⦂ A -- ⇒-I ⊢ƛ : ∀ {Γ x N A B} → Γ , x ⦂ A ⊢ N ⦂ B ------------------- → Γ ⊢ ƛ x ⇒ N ⦂ A ⇒ B -- ⇒-E _·_ : ∀ {Γ L M A B} → Γ ⊢ L ⦂ A ⇒ B → Γ ⊢ M ⦂ A ------------- → Γ ⊢ L · M ⦂ B -- ℕ-I₁ ⊢zero : ∀ {Γ} -------------- → Γ ⊢ `zero ⦂ `ℕ -- ℕ-I₂ ⊢suc : ∀ {Γ M} → Γ ⊢ M ⦂ `ℕ --------------- → Γ ⊢ `suc M ⦂ `ℕ -- ℕ-E ⊢case : ∀ {Γ L M x N A} → Γ ⊢ L ⦂ `ℕ → Γ ⊢ M ⦂ A → Γ , x ⦂ `ℕ ⊢ N ⦂ A ------------------------------------- → Γ ⊢ case L [zero⇒ M |suc x ⇒ N ] ⦂ A ⊢μ : ∀ {Γ x M A} → Γ , x ⦂ A ⊢ M ⦂ A ----------------- → Γ ⊢ μ x ⇒ M ⦂ A

Each type rule is named after the constructor for the corresponding term.

Most of the rules have a second name, derived from a convention in logic, whereby the rule is named after the type connective that it concerns; rules to introduce and to eliminate each connective are labeled `-I`

and `-E`

, respectively. As we read the rules from top to bottom, introduction and elimination rules do what they say on the tin: the first *introduces* a formula for the connective, which appears in the conclusion but not in the premises; while the second *eliminates* a formula for the connective, which appears in a premise but not in the conclusion. An introduction rule describes how to construct a value of the type (abstractions yield functions, successor and zero yield naturals), while an elimination rule describes how to deconstruct a value of the given type (applications use functions, case expressions use naturals).

Note also the three places (in `⊢ƛ`

, `⊢case`

, and `⊢μ`

) where the context is extended with `x`

and an appropriate type, corresponding to the three places where a bound variable is introduced.

The rules are deterministic, in that at most one rule applies to every term.

### Example type derivations

Type derivations correspond to trees. In informal notation, here is a type derivation for the Church numeral two,

```
∋s ∋z
------------------ ⊢` -------------- ⊢`
∋s Γ₂ ⊢ ` "s" ⦂ A ⇒ A Γ₂ ⊢ ` "z" ⦂ A
------------------ ⊢` ------------------------------------- _·_
Γ₂ ⊢ ` "s" ⦂ A ⇒ A Γ₂ ⊢ ` "s" · ` "z" ⦂ A
---------------------------------------------- _·_
Γ₂ ⊢ ` "s" · (` "s" · ` "z") ⦂ A
-------------------------------------------- ⊢ƛ
Γ₁ ⊢ ƛ "z" ⇒ ` "s" · (` "s" · ` "z") ⦂ A ⇒ A
------------------------------------------------------------- ⊢ƛ
Γ ⊢ ƛ "s" ⇒ ƛ "z" ⇒ ` "s" · (` "s" · ` "z") ⦂ (A ⇒ A) ⇒ A ⇒ A
```

where `∋s`

and `∋z`

abbreviate the two derivations,

```
---------------- Z
"s" ≢ "z" Γ₁ ∋ "s" ⦂ A ⇒ A
----------------------------- S ------------- Z
Γ₂ ∋ "s" ⦂ A ⇒ A Γ₂ ∋ "z" ⦂ A
```

and where `Γ₁ = Γ , "s" ⦂ A ⇒ A`

and `Γ₂ = Γ , "s" ⦂ A ⇒ A , "z" ⦂ A`

. The typing derivation is valid for any `Γ`

and `A`

, for instance, we might take `Γ`

to be `∅`

and `A`

to be ``ℕ`

.

Ch : Type → Type Ch A = (A ⇒ A) ⇒ A ⇒ A ⊢twoᶜ : ∀ {Γ A} → Γ ⊢ twoᶜ ⦂ Ch A ⊢twoᶜ = ⊢ƛ (⊢ƛ (⊢` ∋s · (⊢` ∋s · ⊢` ∋z))) where ∋s = S′ Z ∋z = ZHere are the typings corresponding to computing two plus two:

⊢two : ∀ {Γ} → Γ ⊢ two ⦂ `ℕ ⊢two = ⊢suc (⊢suc ⊢zero) ⊢plus : ∀ {Γ} → Γ ⊢ plus ⦂ `ℕ ⇒ `ℕ ⇒ `ℕ ⊢plus = ⊢μ (⊢ƛ (⊢ƛ (⊢case (⊢` ∋m) (⊢` ∋n) (⊢suc (⊢` ∋+ · ⊢` ∋m′ · ⊢` ∋n′))))) where ∋+ = S′ (S′ (S′ Z)) ∋m = S′ Z ∋n = Z ∋m′ = Z ∋n′ = S′ Z ⊢2+2 : ∅ ⊢ plus · two · two ⦂ `ℕ ⊢2+2 = ⊢plus · ⊢two · ⊢two

In contrast to our earlier examples, here we have typed `two`

and `plus`

in an arbitrary context rather than the empty context; this makes it easy to use them inside other binding contexts as well as at the top level. Here the two lookup judgments `∋m`

and `∋m′`

refer to two different bindings of variables named `"m"`

. In contrast, the two judgments `∋n`

and `∋n′`

both refer to the same binding of `"n"`

but accessed in different contexts, the first where `"n"`

is the last binding in the context, and the second after `"m"`

is bound in the successor branch of the case.

⊢plusᶜ : ∀ {Γ A} → Γ ⊢ plusᶜ ⦂ Ch A ⇒ Ch A ⇒ Ch A ⊢plusᶜ = ⊢ƛ (⊢ƛ (⊢ƛ (⊢ƛ (⊢` ∋m · ⊢` ∋s · (⊢` ∋n · ⊢` ∋s · ⊢` ∋z))))) where ∋m = S′ (S′ (S′ Z)) ∋n = S′ (S′ Z) ∋s = S′ Z ∋z = Z ⊢sucᶜ : ∀ {Γ} → Γ ⊢ sucᶜ ⦂ `ℕ ⇒ `ℕ ⊢sucᶜ = ⊢ƛ (⊢suc (⊢` ∋n)) where ∋n = Z ⊢2+2ᶜ : ∅ ⊢ plusᶜ · twoᶜ · twoᶜ · sucᶜ · `zero ⦂ `ℕ ⊢2+2ᶜ = ⊢plusᶜ · ⊢twoᶜ · ⊢twoᶜ · ⊢sucᶜ · ⊢zero

### Interaction with Agda

Construction of a type derivation may be done interactively. Start with the declaration:

```
⊢sucᶜ : ∅ ⊢ sucᶜ ⦂ `ℕ ⇒ `ℕ
⊢sucᶜ = ?
```

Typing C-c C-l causes Agda to create a hole and tell us its expected type:

```
⊢sucᶜ = { }0
?0 : ∅ ⊢ sucᶜ ⦂ `ℕ ⇒ `ℕ
```

Now we fill in the hole by typing C-c C-r. Agda observes that the outermost term in `sucᶜ`

is `ƛ`

, which is typed using `⊢ƛ`

. The `⊢ƛ`

rule in turn takes one argument, which Agda leaves as a hole:

```
⊢sucᶜ = ⊢ƛ { }1
?1 : ∅ , "n" ⦂ `ℕ ⊢ `suc ` "n" ⦂ `ℕ
```

We can fill in the hole by typing C-c C-r again:

```
⊢sucᶜ = ⊢ƛ (⊢suc { }2)
?2 : ∅ , "n" ⦂ `ℕ ⊢ ` "n" ⦂ `ℕ
```

And again:

```
⊢sucᶜ = ⊢ƛ (⊢suc (⊢` { }3))
?3 : ∅ , "n" ⦂ `ℕ ∋ "n" ⦂ `ℕ
```

A further attempt with C-c C-r yields the message:

`Don't know which constructor to introduce of Z or S`

We can fill in `Z`

by hand. If we type C-c C-space, Agda will confirm we are done:

`⊢sucᶜ = ⊢ƛ (⊢suc (⊢` Z))`

The entire process can be automated using Agsy, invoked with C-c C-a.

Chapter Inference will show how to use Agda to compute type derivations directly.

### Lookup is functional

The lookup relation`Γ ∋ x ⦂ A`

is functional, in that for each `Γ`

and `x`

there is at most one `A`

such that the judgment holds:∋-functional : ∀ {Γ x A B} → Γ ∋ x ⦂ A → Γ ∋ x ⦂ B → A ≡ B ∋-functional Z Z = refl ∋-functional Z (S x≢ _) = ⊥-elim (x≢ refl) ∋-functional (S x≢ _) Z = ⊥-elim (x≢ refl) ∋-functional (S _ ∋x) (S _ ∋x′) = ∋-functional ∋x ∋x′

The typing relation `Γ ⊢ M ⦂ A`

is not functional. For example, in any `Γ`

the term `ƛ "x" ⇒ ` "x"`

has type `A ⇒ A`

for any type `A`

.

### Non-examples

We can also show that terms are *not* typeable. For example, here is a formal proof that it is not possible to type the term ``zero · `suc `zero`

. It cannot be typed, because doing so requires that the first term in the application is both a natural and a function:

nope₁ : ∀ {A} → ¬ (∅ ⊢ `zero · `suc `zero ⦂ A) nope₁ (() · _)

As a second example, here is a formal proof that it is not possible to type `ƛ "x" ⇒ ` "x" · ` "x"`

. It cannot be typed, because doing so requires types `A`

and `B`

such that `A ⇒ B ≡ A`

:

nope₂ : ∀ {A} → ¬ (∅ ⊢ ƛ "x" ⇒ ` "x" · ` "x" ⦂ A) nope₂ (⊢ƛ (⊢` ∋x · ⊢` ∋x′)) = contradiction (∋-functional ∋x ∋x′) where contradiction : ∀ {A B} → ¬ (A ⇒ B ≡ A) contradiction ()

#### Quiz

For each of the following, give a type `A`

for which it is derivable, or explain why there is no such `A`

.

`∅ , "y" ⦂ `ℕ ⇒ `ℕ , "x" ⦂ `ℕ ⊢ ` "y" · ` "x" ⦂ A`

`∅ , "y" ⦂ `ℕ ⇒ `ℕ , "x" ⦂ `ℕ ⊢ ` "x" · ` "y" ⦂ A`

`∅ , "y" ⦂ `ℕ ⇒ `ℕ ⊢ ƛ "x" ⇒ ` "y" · ` "x" ⦂ A`

For each of the following, give types `A`

, `B`

, and `C`

for which it is derivable, or explain why there are no such types.

`∅ , "x" ⦂ A ⊢ ` "x" · ` "x" ⦂ B`

`∅ , "x" ⦂ A , "y" ⦂ B ⊢ ƛ "z" ⇒ ` "x" · (` "y" · ` "z") ⦂ C`

#### Exercise `⊢mul`

(recommended)

Using the term `mul`

you defined earlier, write out the derivation showing that it is well typed.

-- Your code goes here

#### Exercise `⊢mulᶜ`

(practice)

Using the term `mulᶜ`

you defined earlier, write out the derivation showing that it is well typed.

-- Your code goes here

## Unicode

This chapter uses the following unicode:

```
⇒ U+21D2 RIGHTWARDS DOUBLE ARROW (\=>)
ƛ U+019B LATIN SMALL LETTER LAMBDA WITH STROKE (\Gl-)
· U+00B7 MIDDLE DOT (\cdot)
≟ U+225F QUESTIONED EQUAL TO (\?=)
— U+2014 EM DASH (\em)
↠ U+21A0 RIGHTWARDS TWO HEADED ARROW (\rr-)
ξ U+03BE GREEK SMALL LETTER XI (\Gx or \xi)
β U+03B2 GREEK SMALL LETTER BETA (\Gb or \beta)
Γ U+0393 GREEK CAPITAL LETTER GAMMA (\GG or \Gamma)
≠ U+2260 NOT EQUAL TO (\=n or \ne)
∋ U+220B CONTAINS AS MEMBER (\ni)
∅ U+2205 EMPTY SET (\0)
⊢ U+22A2 RIGHT TACK (\vdash or \|-)
⦂ U+2982 Z NOTATION TYPE COLON (\:)
😇 U+1F607 SMILING FACE WITH HALO
😈 U+1F608 SMILING FACE WITH HORNS
```

We compose reduction `—→`

from an em dash `—`

and an arrow `→`

. Similarly for reflexive and transitive closure `—↠`

.