Lab 10: Binary Search Trees


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


  • IntelliJ
  • Lab partner


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


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.

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().

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.

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.

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

Step 5: Rotations

Implement left and right rotations. When correct, they should pass their unit tests, and you can also test them in the GUI by clicking on the node that you wish to rotate. As with remove(), these methods return the rebuilt tree nodes.

Step 6: Evaluation

Create trees with 3, 7, and 15 nodes. First, create a balanced tree. Next, erase the tree and create a degenerate tree that is completely linear. Then, use rotations to transform each linear tree into a balanced tree. Record in your evaluation document the number of rotations you needed to perform to balance each tree. Discuss how you identified the need for a rotation when examining each tree.

What to Hand In

Submit and your evaluation document via Teams.


  • To Partially Complete this lab, complete Steps 1, 2, and 3.
  • To Complete this lab, do the above and Steps 4, 5, and 6.