This lesson continues our exploration of sorting by examining a new approach. We’ll start with a simple but powerful observation, and then examine how to build on it to create a complete sorting algorithm. This will also represent our first sorting algorithm that achieves best-case sorting performance! What are we waiting for?
We’ll begin with an observation.
Next, let’s implement
merge on two
int arrays and confirm our hunch about its performance.
Next let’s consider how to design a sorting algorithm that utilize our
We’ll also use this as a chance to point out how we can apply recursive algorithms on arrays, rather than trees, which we’ve used in the past.
Finally, let’s analyze the performance of Mergesort. This is an interesting case! Let’s walk through it carefully.
Create a public class named
Mergesort that provides a single instance method (this is required for testing)
mergesort accepts an
IntArray and returns a sorted (ascending)
IntArray. You should not
modify the passed array.
Mergesort should extend
Merge, and its parent provides several helpful methods:
fun merge(first: IntArray, second: IntArray): IntArray: this merges two sorted arrays into a second sorted array.
fun copyOfRange(original: IntArray, from: Int, to: Int): IntArray: this acts as a wrapper on
java.util.Arrays.copyOfRange, accepting the same arguments and using them in the same way.
(You can't use
java.util.Arrays in this problem for reasons that will become obvious if you inspect the rest of
Note that you do need to use
merge and call it the correct number of times.
This will be tested during grading.
You should use an array of size 1 or 0 as your base case.
Need more practice? Head over to the practice page.