In computer science, a Tree is a widely used abstract data type (ADT), or data structure implementing this ADT, that simulates a hierarchical tree structure, with a root value and subtrees of children with a parent node, represented as a set of linked nodes.

A tree data structure can be defined recursively as a collection of nodes (starting at a root node), where each node is a data structure consisting of a value, together with a list of references to nodes (the “children”), with the constraints that no reference is duplicated, and none points to the root.

*Thanks to Wikipedia for that great definition of Tree data structure in computer science**.*

Trees can be traversed in several ways:

**Pre Order Traversal**: Root, Left, Right.

In our example: A B D H I E J C F G K**In Order Traversal**: Left, Root, Right.

In our example: H D I B J E A F C K G**Post Order Traversal**: Left, Right, Root.

In our example: H I D J E B F K G C A**Level Order Traversal**, also known as Breadth-first search.

In our example: A B C D E F G H I J K

In that tutorial, you are going to learn how to implement these different Tree Traversal Algorithms in Java with recursion and without recursion. Like you could see, recursion solutions are easier than iterative ones. But, you need to understand both solutions because implementing these algorithms are often asked in coding interviews.

For our examples, we will use Java programming language but the logic would be the same for implementing in other languages like C++ or Python.

### Representing a Tree

First step is to represent a Tree. A Tree has nodes. So, we start by defining a *Node* class. A Node will have the following properties:

*data*representing data of the node*left*pointer pointing to the left node*right*pointer pointing to the right node

It gives us the following *Node* class:

For representing a Tree, we will just have to choose a *Node* instance as root of the tree. It gives us the following code for the Tree building:

**Tree Pre Order Traversal with Recursion**

We start by implementing the Tree Pre Order Traversal Algorithm with Recursion. We want to traverse each node of the tree by displaying data for Root, Left and Right node.

So, we need to define a recursive *preOrderTraverse* method taking a *Node* in parameter and making the following operations:

- Displaying data
- Calling
*preOrderTraverse*for the left node - Calling
*preOrderTraverse*for the right node

It gives us the following implementation:

You can discover the implementation and the execution of the **Tree Pre Order Traversal Algorithm with Recursion** in video on YouTube:

### Tree Pre Order Traversal with Iterative solution

Now, things are getting a little more complicated as we will implement with a Tree Pre Order Traversal Algorithm with an Iterative solution. For that, we will need a *Stack* of *Node*.

First, we will push the Tree root in the *Stack*. Then, we will iterate while the *Stack* won’t be empty. We pop all nodes one by one and for each node, we make the following steps:

- Displaying data
- Pushing its right child in the
*Stack* - Pushing its left child in the
*Stack*

It gives us the following implementation:

You can discover the implementation and the execution of the **Tree Pre Order Traversal Algorithm with Iterative solution** in video on YouTube:

### Tree In Order Traversal with Recursion

We implement the Tree In Order Traversal Algorithm with Recursion. We want to traverse each node of the tree starting with Left node, displaying data for Root and finishing with Right node.

So, we need to define a recursive *inOrderTraverse* method taking a *Node* in parameter and making the following operations:

- Calling
*inOrderTraverse*for the left node - Displaying data
- Calling
*inOrderTraverse*for the right node

It gives us the following implementation:

You can discover the implementation and the execution of the **Tree In Order Traversal Algorithm with Recursion** in video on YouTube:

### Tree In Order Traversal with Iterative solution

Now, things are getting a little more complicated as we will implement with a Tree In Order Traversal Algorithm with an Iterative solution. We are going to use a *Stack* of *Node*. We traverse the Tree while the current node is not null or the *Stack* of *Node* is not empty.

At each iteration, we try to reach the most left node from the current node. During this nested ireration, we add each node traversed in the *Stack* of *Node*. At the end of this iteration, current node is null. So, we pop a *Node* from the *Stack* and we display its data. Finally, Now, we visit the right subtree.

It gives us the following implementation:

You can discover the implementation and the execution of the **Tree In Order Traversal Algorithm with Iterative solution** in video on YouTube:

### Tree Post Order Traversal with Recursion

We implement the Tree Post Order Traversal Algorithm with Recursion. We want to traverse each node of the tree starting with Left node, continuing with Right Node and then displaying data for Root.

So, we need to define a recursive post*OrderTraverse* method taking a *Node* in parameter and making the following operations:

- Calling post
*OrderTraverse*for the left node - Calling post
*OrderTraverse*for the right node - Displaying data

It gives us the following implementation:

You can discover the implementation and the execution of the **Tree Post Order Traversal Algorithm with Recursion** in video on YouTube:

### Tree Post Order Traversal with Iterative solution

Now, things are getting a little more complicated as we will implement with a Tree Post Order Traversal Algorithm with an Iterative solution. We start by creating two *Stack* of *Node* which will name nodeStack1 and nodeStack2. We push the Tree root in the nodeStack1.

We iterate while the first stack is not empty. At each iteration, we pop an item from nodeStack1 and we push it to nodeStack2. Then, we push left and right children of popped item to nodeStack1.

Then, in a second loop, we print data all the elements of nodeStack2 . This gives us the following code:

You can discover the implementation and the execution of the **Tree Post Order Traversal Algorithm with Iterative solution** in video on YouTube:

### Tree Level Order Traversal

Finally, we are going to implement Tree Level Order Traversal Algorithm. This algorithm is also known as Breadth-First Search. We need to use an Iterative solution. The solution uses a *Queue* of *Node*. We add the Tree root.

Then, we iterate while *Queue* is not empty. We dequeue a node and we print the data. Then, we add children nodes if not null, left in first and right in second.

It gives us the following implementation:

You can discover the implementation and the execution of the **Tree Level Order Traversal Algorithm** in video on YouTube:

### Conclusion

This article will have allowed you to discover the main Algorithms for Tree Traversal with their implementation in Java. The complete source of the Tree class with the main method calling all the methods presented is available just below:

To discover more tutorials, don’t hesitate to visit the SSaurel’s Channel on YouTube:

If you want to discover some books to learn Java programming, I advice you to read the following article with my selection of the Top 6 Best Books for Java programming :