In earlier article “Introduction to Threaded Binary Tree” we have seen what is threaded binary tree, types of it and what advantages it has over normal binary tree.

In this article we will see the complete implementation of double threaded binary tree. ( Click here to read about “single threaded binary tree”)

Image Source : http://web.eecs.umich.edu/~akamil/teaching/su02/080802.ppt

**Double threaded:** each node is threaded towards both the in-order predecessor and successor (left **and** right) means all right null pointers will point to inorder successor **AND** all left null pointers will point to inorder predecessor.

**Implementation:**

Let’s see how the Node structure will look like

class Node { int data; int leftBit; int rightBit; Node left; Node right; public Node(int data) { this.data = data; } }

If you notice we have two extra fields in the node than regular binary tree node. leftBit and rightBit. Let’s see what these fields represent.

leftBit=0 | left reference points to the inorder predecessor |

leftBit=1 | left reference points to the left child |

rightBit=0 | right reference points to the inorder successor |

righBit=1 | right reference points to the right child |

Let’s see why do we need these fields and why do we need a dummy node when If we try to convert the normal binary tree to threaded binary

Now if you see the picture above , there are two references left most reference and right most reference pointers has nowhere to point to.

** Need of a Dummy Node**: As we saw that references left most reference and right most reference pointers has nowhere to point to so we need a dummy node and this node will always present even when tree is empty.

In this dummy node we will put ** rightBit = 1** and its right child will point to it self and

**, so we will construct the threaded tree as the left child of dummy node.**

*leftBit = 0*Let’s see how the dummy node will look like:

Now we will see how this dummy node will solve our problem of references left most reference and right most reference pointers has nowhere to point to.

Now we will see the some operations in double threaded binary tree.

**Insert():**

The insert operation will be quite similar to Insert operation in Binary search tree with few modifications.

- To insert a node our first task is to find the place to insert the node.
- First check if tree is empty, means tree has just dummy node then then insert the new node into left subtree of the dummy node.
- If tree is not empty then find the place to insert the node, just like in normal BST.
- If new node is smaller than or equal to current node then check if
, if yes then we have found the place to insert the node, it will be in the left of the subtree and if*leftBit =0*then go left.*leftBit=1* - If new node is greater than current node then check if
, if yes then we have found the place to insert the node, it will be in the right of the subtree and if*rightBit =0*then go right.*rightBit=1* - Repeat step 4 and 5 till the place to be inserted is not found.
- Once decided where the node will be inserted, next task would be to insert the node. first we will see how the node will be inserted as left child.

n.left = current.left; current.left = n; n.leftBit = current.leftBit; current.leftBit = 1; n.right = current;

see the image below for better understanding

- To insert the node as right child.

n.right = current.right; current.right = n; n.rightBit = current.rightBit; current.rightBit = 1; n.left = current;

see the image below for better understanding.

**Traverse():**

Now we will see how to traverse in the double threaded binary tree, we do not need a recursion to do that which means it won’t require stack, it will be done n one single traversal in O(n).

Starting from left most node in the tree, keep traversing the inorder successor and print it.(click here to read more about inorder successor in a tree).

See the image below for more understanding.

**Complete Code:**

**Output:**

1 2 4 10 12 13 15