# Tree Recursion

In the previous examples we saw recursive functions that call themselves one time within the code. This type of recursion is called *linear recursion*, where head and tail recursion are two specific types of linear recursion.

In this section we will investigate another type of recursion called *tree recursion*, which occurs when a function calls itself two or more times to solve a single problem. To illustrate tree recursion, we will use a simple recursive function `MAX`

, which finds the maximum of
$ N $ elements in an array. To calculate the maximum of
$ N $ elements we will use the following recursive algorithm.

- Compute the maximum of the first
$ N/2 $ elements and store in
`MAX1`

. - Compute the maximum of the last
$ N/2 $ elements and store in
`MAX2`

. - Compare
`MAX1`

and`MAX2`

to find the maximum of all elements.

Our process recursively decomposes the problem by searching for the maximum in the first $ N/2 $ elements and the second $ N/2 $ elements until we reach the base case. In this problem, the base case is when we either have 1 or 2 elements in the array. If we just have 1, we return that value. If we have 2, we return the larger of those two values. An overview of the process is shown below.

The pseudocode for the algorithm is shown below.

```
function MAX(VALUES, START, END)
print "Called MAX with start = " + START + ", end = " + END
if END – START = 0
return VALUES[START]
else if END – START = 1
if VALUES(START) > VALUES(END)
return VALUES[START]
else
return VALUES[END]
end if
else
MIDDLE = ROUND((END – START) / 2)
MAX1 = MAX(VALUES, START, START + MIDDLE – 1)
MAX2 = MAX(VALUES, START + MIDDLE, END)
if MAX1 > MAX2
return MAX1
else
return MAX2
end if
end if
end function
```

The following block shows the output from the `print`

line in the `MAX`

function above. The initial call to the function is `MAX(VALUES, 0, 15)`

.

```
Called MAX with start = 0, end = 7
Called MAX with start = 0, end = 3
Called MAX with start = 0, end = 1
Called MAX with start = 2, end = 3
Called MAX with start = 4, end = 7
Called MAX with start = 4, end = 5
Called MAX with start = 6, end = 7
Called MAX with start = 8, end = 15
Called MAX with start = 8, end = 11
Called MAX with start = 8, end = 9
Called MAX with start = 10, end = 11
Called MAX with start = 12, end = 15
Called MAX with start = 12, end = 13
Called MAX with start = 14, end = 15
```

As you can see, `MAX`

decomposes the array each time it is called, resulting in 14 instances of the `MAX`

function being called. If we had performed head or tail recursion to compare each value in the array, we would have to have called `MAX`

16 times. While this may not seem like a huge savings, as the value of
$ N $ grows, so do the savings.