Recently I was working through some problems related to the Untyped Lambda Calculus and was getting tired of reducing expressions by hand. I tried writing a small evaluator to help, and was surprised how straightforward it turned out to be. The evaluator is only 40 lines or so - easily small enough to fit in a blog post. So here it is! The source for this post is here.

The first thing we need is a representation for lambda terms. The lambda calculus is very simple: we have lambda abstraction (i.e. functions), variables, and applications.

Thus the Church numeral one `\f. \x. f x`

becomes:

`Lam "f" (Lam "x" (App (Var "f") (Var "x")))`

We use `String`

for variable bindings, for simplicity.

What we want by the end is a function `nf`

which computes the normal form of a given lambda expression - that is, the result when we reduce it as much as possibe. `Context`

contains the free variables in scope for a given expression. It’s simply a map from variable name to the expression bound to that variable. When evaluating a full expression we’ll typically start with a empty context (`mempty`

).

`reduceList`

produces a list of consecutive reductions of the expression, with the last one at the front. To compute the normal form we just take this first element.

```
type Context = [(String, Expr)]
reduceList :: Context -> Expr -> [Expr]
reduceList ctx expr = go [expr]
where go (e : es) = let e' = reduce ctx e
in if e' == e
then (e : es)
else go (e' : e : es)
```

You can see that we build up a list of reduced expressions, stopping when reducing the expression no longer changes it. If the expression does not reduce to normal form (e.g. Ω) then this function will not terminate.

The actual work happens in `reduce`

:

```
reduce :: Context -> Expr -> Expr
reduce ctx (Var v) = fromMaybe (Var v) (lookup v ctx)
reduce ctx (Lam v a) = Lam v (reduce ctx a)
reduce ctx (App (Lam v a) b) = substitute v a b
reduce ctx (App a b) = App (reduce ctx a) (reduce ctx b)
```

`reduce`

applies one round of beta reduction to the expression. Symbolically, beta reduction is defined as `(\x. e) a ↝ e[a/x]`

. This means that when we have an application of a lambda abstraction with a variable `x`

over an expression `e`

to another lambda expression `a`

, we can reduce it to `e`

with all instances of `x`

replaced by `a`

. The only thing we need to be sure of is that `x`

does not appear as a free variable in `a`

.

So what `reduce`

does depends on the type of expression:

- If it’s a variable, we look up its value in our context and replace it with the value.
- If its a function, we reduce the inner expression it contains.
- If it’s an application of a function to another expression, we substitute every occurrence of the variable bound by the function with the expression being applied.
- For any other application, we just reduce both inner expressions.

The final piece we need is `substitute`

, which performs the variable substitution.

```
substitute :: String -> Expr -> Expr -> Expr
substitute v a b = go a
where go (Var v') | v' == v = b
| otherwise = Var v'
go (Lam v' e) | v' == v = Lam v' e
| otherwise = Lam v' (go e)
go (App x y) = App (go x) (go y)
```

`substitute`

replaces all instances of a variable with an expression. To avoid variable capture, it won’t recurse inside a lambda abstraction of the same variable name.

Some examples:

```
substitute "x" (Var "x") e == e
substitute "x" (App (Var "f") (Var "x")) e == App (Var "f") e
substitute "x" (Lam "y" (Var "x")) e == Lam "y" e
substitute "x" (App (Var "x") (Lam "x" (Var "x"))) e == App e (Lam "x" (Var "x"))
```

That’s it! We can now define and reduce some lambda expressions.

```
> nf mempty (App (Lam "x" (Var "x")) (Var "y"))
Var "y"
> nf mempty (App (App (Lam "f" (Lam "x" (App (Var "f") (Var "x")))) (Lam "e" (Var "e"))) (Var "t"))
Var "t"
```

These aren’t very nice to write by hand, but parsing untyped lambda calculus is quite straightforward. I might tackle that in a future blog post.

Since writing this evaluator I’ve been experimenting with the other variants of lambda calculus, in particular the different type systems T, F etc. I’ll probably write at least another blog post on what I’ve learned but until then the experiments are on GitHub. There’s also an online version which you can use to play around with the different lambda calculi here.