There are many ways to categorize a recursive function. Listed below are some of the most common.

### Linear Recursive

A linear recursive function is a function that only makes a single call to itself each time the function runs (as opposed to one that would call itself multiple times during its execution). The factorial function is a good example of linear recursion.

Another example of a linear recursive function would be one to compute the
square root of a number using Newton's method (assume `EPSILON` to be
a very small number close to 0):

### Tail recursive

Tail recursion is a form of linear recursion. In tail recursion, the recursive call is the last thing the function does. Often, the value of the recursive call is returned. As such, tail recursive functions can often be easily implemented in an iterative manner; by taking out the recursive call and replacing it with a loop, the same effect can generally be achieved. In fact, a good compiler can recognize tail recursion and convert it to iteration in order to optimize the performance of the code.

A good example of a tail recursive function is a function to compute the GCD, or Greatest Common Denominator, of two numbers:

### Binary Recursive

Some recursive functions don't just have one call to themself, they have two (or more). Functions with two recursive calls are referred to as binary recursive functions.

The mathematical combinations operation is a good example of a function
that can quickly be implemented as a binary recursive function. The number
of combinations, often represented as *nCk* where we are choosing n
elements out of a set of k elements, can be implemented as follows:

### Exponential recursion

An exponential recursive function is one that, if you were to draw out a
representation of all the function calls, would have an exponential
number of calls in relation to the size of the data set (exponential
meaning if there were *n* elements, there would be *O*(*a*^{n}) function
calls where a is a positive number).

A good example an exponentially recursive function is a function to compute
all the permutations of a data set. Let's write a function to take an
array of `n` integers and print out every permutation of it.

To run this function on an array `arr` of length `n`, we'd do
`print_permutations(arr, n, 0)` where the `0 tells it to start
at the beginning of the array.
`

### Nested Recursion

In nested recursion, one of the arguments to the recursive function is
the recursive function itself! These functions tend to grow extremely fast.
A good example is the classic mathematical function, "Ackerman's function.
It grows very quickly (even for small values of x and y, Ackermann(x,y) is
extremely large) and it cannot be computed with only definite iteration
(a completely defined `for()` loop for example); it requires indefinite
iteration (recursion, for example).

Try computing ackerman(4,2) by hand... have fun!

### Mutual Recursion

A recursive function doesn't necessarily need to call itself. Some recursive functions work in pairs or even larger groups. For example, function A calls function B which calls function C which in turn calls function A.

A simple example of mutual recursion is a set of function to determine
whether an integer is even or odd. How do we know if a number is even?
Well, we know 0 is even. And we also know that if a number *n* is even,
then *n* - 1 must be odd. How do we know if a number is odd? It's not even!

I told you recursion was powerful! Of course, this is just an illustration. The above situation isn't the best example of when we'd want to use recursion instead of iteration or a closed form solution. A more efficient set of function to determine whether an integer is even or odd would be the following: