CSCI 151 Lab 7: The Sortimator
Overview
In this lab, we will implement multiple sorting algorithms and compare their perfomance.Step 1: Setup
- Download the skeleton for this project.
- Unpack the code into a new Eclipse Java project.
- Add in the JUnit library to your project settings if necessary.
- Run the
Sortimator.java
file in thesorting.gui
package and verify that the GUI is displayed. - Click the Scramble and then Sort buttons to watch an animation of the GnomeSort algorithm.
GnomeSorter.java
. This is an
example algorithm demonstrating elements that you should use in your
implementations below. Each algorithm will need to implement the
sortAlgorithm
method, which takes
an ArrayList
to be sorted.
First, we can access the elements in the list with the get
method,
and determine its size with the size
method. However,
notice that we do not use the set
element of the list. Instead,
we call our own set
method, which takes the list to be set, the
index that will be set, and the element to set in the index location. This
roundabout method is used to assist with the animation. You will need to use
this method in all of your implementations.
Next, since we have an ArrayList
of generic elements, we
need to call the compareTo
method. This will return an
integer, equal to 0 if the two elements are the same, -1 if first is
smaller than the second, and 1 if the first is larger than the second,
according to whatever ordering scheme is defined. We will want our
resulting array to be sorted from smallest to largest.
Also note that there is a swap going on in this algorithm. You might consider implementing
a swap
method as you code below to make your life easier.
Step 2: InsertionSorter
Your first sorting algorithm to implement is insertion sort. Since we already implemented this algorithm together in class, the focus is on becoming familiar with the particular framework used for this lab.
Create a new class called InsertionSorter
. To fit into the Sortimator
hierarchy, it will need to extend the generic Sorter
class. Also, the
generic type E
will need to extend the Comparable
interface.
The name of your class should be something like
InsertionSorter<E extends Comparable<E>> extends Sorter<E>
Step 2.1: Implementation
As discussed in class, insertion sort can be implemented with the following algorithm:- For each element in the list:
- If the current element is smaller than the element to its left, swap them.
- If you just made a swap, repeat this check for the next two elements to the left.
Step 2.2: Testing
Run your code through the SorterTester
suite to make
sure your implementation has the correct behavior.
Step 3: BubbleSorter
Bubble sort is known for the simplicity of its code. Repeated passes
through the data quickly push the largest elements to the end, and
slowly drag the smallest elements to the front of the list.
The name of your class should be
BubbleSorter<E extends Comparable<E>> extends Sorter<E>
Step 3.1: Implementation
Bubble sort can be implemented with the following algorithm:- Repeatedly scan through the whole list from left to right.
- When you find elements out of order, swap them into correct order.
Step 3.2: Testing
Run your code through the SorterTester
suite to make
sure your implementation has the correct behavior.
Step 4: MergeSorter
Merge sort uses recursion to repeatedly split the given list into smaller lists,
sort the smaller lists, and then combine the sorted sublists into one sorted list.
The name of your class should be
MergeSorter<E extends Comparable<E>> extends Sorter<E>
Step 4.1: Implementation
First, you will need to create amergeSortHelper
method. During the recursion, we need to keep track of the start and
end indicies of the current sublist. These indices should be
additional parameters to mergeSortHelper
along with the
list. As we did with binary search, the sublist should include
the start
index and extend up to but not including
the end
index. So, sortAlgorithm
will call
the mergeSortHelper
method with a starting index of 0 and
an end index equal to the size()
of the list.
mergeSortHelper
has the following structure:
- If the current sublist is more than one element long:
- Split the elements in half and call
mergeSortHelper
on each sublist - Merge together the two sublists, storing the resulting merged elements back in the original array.
- Split the elements in half and call
To complete this method, we need a merge
method, which
takes the same parameters as mergeSortHelper
(a list,
start, and end indices), and merges the two half sublists into one,
assuming they are already sorted.
- Create a new list to hold the merged elements.
- Create indices
i
andj
to iterate through the two sublists, withi
beginning atstart
, andj
beginning at(start+end)/2
. - Compare the elements at
i
andj
, adding the smaller one to the new list. - Repeat this comparison and setting until you reach the end of one sublist.
- Add any remaining elements from either sublist to the end of the new list.
- Finally, copy the merged elements from the new list back into the original array.
Step 4.2: Testing
Run your code through the SorterTester
suite to make
sure your implementation has the correct behavior.
Step 5: QuickSorter
Whereas merge sort has an easy journey down the recursion and the real
work happens on the way back up while merging,
quicksort reverses this scheme. Before recursing, quicksort
partitions the elements of the list, into two (ideally equal-sized)
portions, placing the elements smaller than a chosen pivot
element to the left and those elements larger to the right. These
sublists will be semi-sorted, and then repeatedly partitioned until
all elements are in the correct order.
Create a QuickSorter
class to implement quicksort.
Step 5.1: Implementation
Again, we will need a recursive helper function, augmenting with the start (inclusive) and end (exclusive) indices of the sublist.quickSortHelper
has the following structure:
- If the current sublist has more than one element:
partition
the elements into two sublists, returning the resulting position of the pivot element.- Recursively apply
quickSortHelper
to the two sublists.
The partition
method should have the same parameters as the
quickSortHelper
method, and works as follows:
- Select the last element of the sublist as the
pivot
element. - Scan all the other elements in the list, and ensure that an element is swapped into the front portion of the list if it is smaller than the pivot element.
- This can be accomplished by remembering how many elements so far have been found to be smaller than the pivot, and placing the next encountered smaller element at this count spot.
- Finally, swap the partition to the spot in the list directly after all of the elements smaller than it.
The partition
method will need to return the location of
the pivot element after all swaps have been made, as this is the
dividing line between the two sublists.