Trees in Java: How to Implement a Binary Tree?
In the tech world, the word “trees” stands for a data structure type. This type of data structure is different from arrays, linked lists, and others. But the most common type of tree used by developers is the binary tree.
You have landed on just the right place to seek all the information about trees and in specific, binary trees.
With help of this article, you will be able to calculate and analyze the top view of the binary tree, the left view of the binary tree, and the right view of the binary tree appropriately.
Do you know the Binary tree and its understanding is a major concept to crack coding interviews and exams?
In this article, we have explained what binary trees are, their types, and their implementation in detail. But before moving straight to the binary trees, let’s talk about trees in brief.
What are trees
Trees are non-linear data structures!
The trees are different from usual data structures due to their hierarchical data storage technique.
Just like a tree, each element in a tree data structure has one or two child nodes resembling the branches of the tree.
You can store and analyze data based on their hierarchical order with the help of a tree data structure.
Each type of tree comes with three main components for every element they store. It includes data, a pointer to the left node, and another pointer to the right node/child.
But there are various properties of trees such as element storage, placement of nodes, number of nodes, views, data implementation,and others on which you can determine their different types of trees.
One of the major categories of trees based on node placement is binary.
Binary trees are data structures where each element have a maximum of two children attached to it.
Can you think of ways in which binary trees can be further classified into types?
Let’s have a glance at the types of binary trees.
Types of Binary trees
A binary tree is a name you must have heard!
Have you ever thought that on what terms can you divide binary trees into different categories?
Well, the parameter is the connection of elements from different nodes and based on this parameter, the binary trees are divided into three major categories:
- Full binary
No space for new nodes!
In full binary trees, each node of the tree is either attached to two or simply zero child nodes.
This indicates that the tree is filled and there is no node with one child node attached to it.
- Complete binary trees
Every level is filled!
In the case of complete binary trees, every level of the binary trees is filled. It means that all the nodes in each level are connected to two or zero child nodes.
However, note that the end of the last level might not be filled completely!
- Perfect Binary trees
Perfect element storage and connection!
The perfect binary trees are the ones where each level has filled nodes. This means that all the nodes on a certain level have two child nodes attached to them.
Also, all the child nodes are on the same level in a perfect binary tree.
After knowing the types of binary trees, you can now identify the binary tree easily. Let’s now discuss another important component i.e. implementation of binary trees!
How is the Binary tree implemented in Java?
Do you know that in Java, the binary tree nodes are implemented through a specific class and not a function?
These nodes can store different types of data. The data types stored in nodes can include string, integer, float, char, or double.
Once you decide the data type you wish to store, all you need is to select the method of implementation. There are two major ways in which you can implement binary trees in Java. Following are the methods to implement binary trees in Java:
- Node representation
In this method, you can add the nodes of a binary tree as per your requirement throughout the code.
It means that this method of implementation is dynamic and elements are stored in an adequate dynamic manner.
This method of data implementation is used when the database is huge and the number of elements is not fixed.
- Array representation
This method is different due to static memory allocation. In this case, you will not be able to change or add the number of nodes.
In short, the memory allocation, in this case, is done during the initial stage, and hence, you will have to face space issues afterward.
However, in case you have a fixed database that you need to store in the data structure, storing data through this method is more efficient and convenient. Also, the added advantage of ease and convenience in accessing a certain element from the tree comes with array representation.
Let’s take an example and clarify the concept of Binary tree implementation in java further.
Say, that you need to store the names of your employees in a binary tree format.
Hence, in this case, you will have to store data in the string or simply Char data type. After this, you will have to create a class. This class must accept char data types as parameters.
Once you declare the variables and insert the values, You can then create a simple traverse tree that will help you in showing the elements at the nodes.
Note that you will have to put the nodes one by one and then place(locate) them at adequate values throughout the class.
Now that you pass this function through a class and appropriate algorithm, you will get the data(names) of your employees displayed hierarchically.
Can you think of the method that is best suitable for this purpose or this example? Let us make it clear, you can apply both representations in this example.
For a definite number of employees (Static or array representation) or even by keeping the scope of adding new employees (Node or dynamic representation)
Would you like to give it a try on your own?
Build a code with both methods and compare their work to make concepts more clear!
Winding up
Once the concept of binary tree implementation is clear to you, it will be easier for you to store your data conveniently.
It can also be used to analyze the top view of the binary tree and also the right view of the binary tree.
Hopefully, now, you can easily implement your binary tree from two different methods with efficiency!