Lab 10: Binary Search Trees

Overview

In this lab, we will implement a Binary Search Tree and visualize the processes of insertion, deletion, and rotation.

Materials

IntelliJ
Lab partner

Setup

Download the skeleton for this project.
Unpack the code into a new IntelliJ Java project.

Description

We can efficiently store information with arrays and linked lists, but determining if an element is present could take a linear search through each element if the data is not sorted. At best, sorting will take O(n log n), and so we explore an alternative here which incorporates the idea of binary search into a linked structure of nodes.

Note: Our items to be stored and compared in this lab will be strings. For testing purposes, I recommend using single letters as entry, however, full words can also be used. If you use numbers, they will be sorted in alphabetic order, not numerical order.

`Optional` vs `null`

One way to implement a TreeNode in Java is to use null for the left and right children when these children are empty. However, this opens up the possibility for a NullPointerException if we code incorrectly, and we won’t know if the exception is because of this or some other unexpected null in our algorithm.

In this lab, we will use a special class in Java called Optional. This class can be used in lieu of null, so you know exactly what error you are getting and why. We wrap all of our TreeNode objects in an Optional object. So, instead of saying left == null, we would ask ‘left.isPresent()’. If left exists, then we can get the TreeNode by saying left.get().

Important: To make a new child, we would say something like left = Optional.of(new TreeNode(value)).

Methods that remain to be implemented in the TreeNode class have been marked with TODO for easy identification.

Step 1: `insert()` and `contains()`

Use recursion to complete the insert() and contains() methods in the TreeNode class. Both of them will need to use the result of value.compareTo(this.value) method to determine if the parameter is less than, equal to, or greater than the value at the current TreeNode.

The test case BinarySearchTreeTester.test1() should pass if your solutions are correct.

Step 2: Tree Statistics and Visualization

Complete the size(), getMin(), getMax(), and height() methods in the TreeNode class.

Note: You should complete these methods in the order above, this is the order they are accessed in the GUI for display.

Then run BinaryTreeApp. As you insert nodes into your tree, you should see the statistics updated on the right. Make sure the values are correct by experimenting with different tree structures.

Step 3: Traversals

Complete the preOrder(), postOrder(), and inOrder() methods in the TreeNode class. The op parameter is a Consumer object that performs the op.accept(value) operation on the current value either before, after, or in-between using recursion to traverse the children.

These methods should pass their unit tests, and also you can test them in BinaryTreeApp.

Step 4: Deletion

Implement the remove() method. Note that it does not return the removed node; it returns the node upon which it was invoked, and rebuilds the tree as it exits from its recursive calls. Follow the comments carefully.

Note: Somewhere in your method, you will probably write a line similar to left = left.get().remove(target);

It should pass its unit tests and again is testable on the GUI, by clicking on nodes you wish to remove.

Grading

To Complete this lab, complete Steps 1-4.