# 3.9. Recursive Functions¶

## 3.9.1. The Y Fixed-point Combinator¶

To turn the \(\lambda\) calculus into a "real" programming language, we need to be able to manipulate, we saw in the previous section that we could appropriately define boolean constants (true, false), conditionals (if-then-else), logical operators (and, or, not), integers (0, 1, 2, 3, etc.), and arithmetic operators (\(+\), \(-\), etc.).

However, one thing is missing. We still need to be able to define
recursive functions (factorial, etc.). But to recur, we need a "name"
by which we can refer to the function we are creating within the
function we are creating. And the \(\lambda\) calculus does not
give us global names. Instead we only have a variable that represents
the parameter in a function abstraction. So is there a way out of
this dilemma? The answer is "yes", and it's called a **fixed point
combinator**.

For any \(f\) and \(x\), if \(f(x) = x\) then \(x\) is
called a **fixed point** of the function \(f\).

Examples to consider when the functions are functions of real numbers:

- Can you find one or more fixed points for the function \(f(t) = t^2\)?
- Can you find one or more fixed points for the function \(f(t) = 1\)?
- Can you find one or more fixed points for the function \(f(t) = t+1\)?

When we are dealing with functions of real numbers, the "algorithm" to find a fixed point to solve the equation \(f(x) = x\). If a solution can be found, the function has a fixed point; otherwise it doesn't. fixed point of any numerical function?

Is there a similar technique to find the fixed point of any \(\lambda\) calculus function? Consider a function that we call \(Y\) for historical reasons. It is defined as follows:

\(Y\) will find the *fixed point* of any function F. That is, for any
function F, \((F \; (Y \; F)) = (Y \; F)\). To see this, note that the substitution dictated by
\(\beta\) reduction leads us to:

Now using the IF-THEN-ELSE, MULT, ISZERO, and PRED functions that were defined within the \(\lambda\) calculus in the previous section, we can define a new function:

This new function resembles what we would normally think of as a
recursively defined factorial function *except* it uses a parameter
\(g\) instead of a globally defined name \(g\). Hence it is a
valid definition in the \(\lambda\) calculus. Although valid, it
is also unfortunately not a recursive factorial function. The amazing thing, however, is that, if we apply \(Y\) to this function, that is:

we get the factorial function. It may take awhile to convince yourself of this. Try carrying out the \(\beta\) reductions that would come into play when

is evaluated, and you should see how the Church numeral \(SIX\) is eventually produced.

## 3.9.2. Identifying Fixed Point Combinators¶

Although the function \(Y\) defined above is a famous fixed-point combinator, there are also many other fixed-point combinators, that is, functions \(Z\) with the property that:

for all functions \(F\). This problem will give you practice with identifying other fixed-point combinators.

To reduce syntactic clutter in this problem, we will take some shortcuts in writing \(\lambda\) expressions. First, we will drop all but the first \(\lambda\) and all but the last dot for (curried) functions with two or more parameters. So, for example, we will use:

as an abbreviation for:

Second, to cut down on parentheses, we will use \((u\ v\ w\ x\ y\
z)\) as an abbreviation for \((((((u\ v)\ w)\ x)\ y)\ z)\). In
essence, we are making function application left-associative. **This
notation is to be used only for this review problem. Do NOT use it
for any assignments, exams, or other review problems.**