Lab 8: The Sortimator

Overview

In this lab, we will implement multiple sorting algorithms and compare their perfomance.

Materials

• IntelliJ
• Lab partner

Setup

1. Download the skeleton for this project.
2. Unpack the code into a new InteliJ Java project.
3. Add in the JUnit and JavaFX libraries to your project settings if necessary.
4. Run the Sortimator.java file in the sorting.gui package and verify that the GUI is displayed.
5. Click the Scramble and then Sort buttons to watch an animation of the GnomeSort algorithm.

GnomeSort

Take a look at the code inside GnomeSorter.java. This is an example algorithm demonstrating elements that you should use in your implementations below. Each algorithm below will need to implement the sortAlgorithm method, which brings in 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.

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, negative if first is smaller than the second, and positive 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.

Step 1 - BubbleSorter

Bubble sort is known for its simplicity of 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.

Create a new class called BubbleSorter. 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

BubbleSorter<E extends Comparable<E>> extends Sorter<E>

Step 1.1 - Implementation

BubbleSort can be implemented with the following algorithm.

• Scan through the whole list from left to right.
• When you find elements out of order, swap them into correct order.
• If any elements were found out of order during this scan, repeat.

To save time, each scan can reduce the elements it examines by one, since on the first pass, we can guarantee that the highest element will be in the right location, and on the second pass, the second-highest element will be in the right location, etc.

Step 1.2 - Testing

Run your code through the SorterTester suite to make sure your implementation has the correct behavior.

Step 2 - MergeSorter

MergeSort 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 2.1 - Implementation

First, you will need to create a void mergeSortHelper(ArrayList<E> array, int start, int end) method. In order to do recursion, we will need to track the start and end indices of our subarrays. The start and end should be additional parameters along with the list. Use end as we have in other contexts, to be the stopping index, going up to but not including this index.

So, our sortAlgorithm will call the mergeSortHelper method with start as 0 and end as the size of the list.

mergeSortHelper has the following structure:

• If the start and end are more than one element apart
  • Find the midpoint index between start and end. The midpoint index should divide start and end in half.
  • Call mergeSortHelper recursively twice; once on the first half of the array, and once on the second half. Use the start, end, and midpoint indices to structure the recursive calls properly.
  • Merge together the two sorted subarrays.

To complete this method, we need a void merge(ArrayList<E> array, int start, int end) method. The most straightforward implementation involves using a Queue. In Java 21, you should use the ArrayDeque a double-ended queue which can be found in the java.util package:

• add() each element of the first half of the subarray into a queue.
• add() each element of the second half of the subarray into a different queue.
• For each element of the subarray
  • if the second queue is empty, or if the first queue is not empty and its element() value is less than or equal to the element() value of the second queue
    • remove() the value from the first queue and store it at this location in the array with set.
  • Otherwise, remove() the value from the second queue and store it at this location in the array with set.

Step 2.2 - Testing

Run your code through the SorterTester suite to make sure your implementation has the correct behavior.

Step 3 - QuickSorter

Whereas MergeSort was an easy journey down the recursion but complicated merging back up, QuickSort reverse this scheme. Before recursing, QuickSort partitions the elements of the list, hopefully into two equal-sized portions, placing the elements smaller than a randomly chosen pivot element to the left and those elements larger to the right. These subarrays will be semi-sorted, and then repeatedly partitioned until all elements are in the correct order.

The name of your class should be

QuickSorter<E extends Comparable<E>> extends Sorter<E>

Step 3.1 - Implementation

Again, we will need a recursive helper function, augmenting with the start and end of the subarray. void quickSortHelper(ArrayList<E> array, int start, int end) has the following structure:

• If the start and end are more than one element apart
  • Partition the elements
  • Recursively apply quickSortHelper to the partitioned subarrays

The int partition(ArrayList<E> array, int start, int end) method should have the same parameters as the quickSortHelper method.

• Select the last element of the subarray as the pivot element.
• Initialize a variable to track the total number of elements smaller than the pivot.
• For each subarray element prior to the pivot:
  • If the element is less than the pivot:
    • Swap it so that it winds up early in the subarray, by using the total number of smaller elements we have seen so far to determine its destination index.
    • Increase by one the number of total elements seen that is smaller than the pivot.
• Calculate the final position of the pivot using the total number of elements smaller than it.
• Move the pivot to that final position, and then return that final position, as it represents the division point between the subarrays that must now be recursively sorted.

Step 3.2 - Testing

Run your code through the SorterTester suite to make sure your implementation has the correct behavior.

Step 4 - Evaluation

Describe in your own words the strengths and weaknesses of each of the three implementations above. Use the Sortimator class to run each algorithm 3 times, on a list of size 20. Record the number of Array Updates that each method executes, as found through the GUI.

Grading

• To Complete this lab, complete all 4 Steps.