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Viewed 676 times 0. Try implementing it without even using a stack! However, I believe the iterative algorithm would be clearer if it made a proper distinction between children nodes and popped nodes, as they have a different significance inside the loop. In an Inorder traversal, we process all the nodes of a tree by recursively processing the left subtree, then processing the root, and finally the right subtree. I'm trying to implement an iterative inorder traversal of a binary tree. # else if current node is None, we pop an element from the stack, # print it and finally set current node to its right child, Notify of new replies to this comment - (on), Notify of new replies to this comment - (off), https://en.wikipedia.org/wiki/Tree_traversal, Preorder Tree Traversal | Iterative & Recursive, Find Lowest Common Ancestor (LCA) of Two Nodes in a Binary Tree. One of the most common things we do on a binary tree is traversal. Approach 2 – Iterative implementation of Inorder Traversal. Space Complexity: O(N) – If we have a skewed binary tree, then recursion has to go N nodes deep before it hits the end(or NULL or base case). (40 votes, average: 4.38 out of 5)Loading... Guys please learn both the methods once in my interview the interviewer asked me to write both iterative and recursive approach . This can be seen as this.Operations to perform: <Traverse all the nodes in left subtree> Root <Traverse all the nodes in the right subtree> , true for each node in the tree. Given a binary tree, write iterative and recursive solution to traverse the tree using in-order traversal in C++, Java and Python. Using Stack is the obvious way to traverse tree without recursion. s.push(node) I hadn’t been satisfied with the way in which the iterative solution of inorder binary tree traversal has been explained so far in my searches on the intertubes. Happy coding . Ask Question Asked 2 days ago. An inorder traversal on a BST returns a sorted list of node values. // Recursive function to perform in-order traversal of the tree, // Display the data part of the root (or current node), # Recursive function to perform in-order traversal of the tree, # Display the data part of the root (or current node), // Iterative function to perform in-order traversal of the tree, // start from root node (set current node to root node), // if current node is null and stack is also empty, we're done, // if current node is not null, push it to the stack (defer it). For traversing a (non-empty) binary tree in in-order fashion, we must do these three things for every node N starting from root node of the tree: In normal in-order traversal we visit left subtree before the right subtree. References: https://en.wikipedia.org/wiki/Tree_traversal. Thanks for sharing your concerns. Space Complexity: O(N) – If the binary tree is skewed, then we have a stack full of all the nodes of the binary tree. Each algorithm has its own benefits and use-cases. These operations can be defined recursively for each node. As we all know, a Binary Tree is a tree made up of nodes and each node can have at most two children. We have updated the pseudocode. In Binary search tree traversals we discussed different types of traversals like inorder, preorder and postorder traversals. We will recursively process the left subtree, then we will process the root node and then finally we will process the right subtree. The time complexity of above solutions is O(n) and space complexity of the program is O(n) as space required is proportional to the height of the tree which can be equal to number of nodes in the tree in worst case for skewed trees. Given a binary tree, write iterative and recursive solution to traverse the tree using in-order traversal in C++, Java and Python. Tree traversal are methods to traverse tree in different ways. The traversal can be done iteratively where the deferred nodes are stored in the stack or it can be done by recursion where the deferred nodes are stored implicitly in the call stack. Below is a simple stack based iterative algorithm to do in-order traversal. while (not s.isEmpty() or node != null) Unlike linked lists, one-dimensional arrays and other linear data structures, which are traversed in linear order, trees may be traversed in multiple ways in depth-first order (pre-order, in-order, and post-order) or breadth-first order (level order traversal). The aim of using a stack is, it gives the same effect as the recursion does because internally recursion stores the recursive stages(the stages it has been through) in the memory as a stack too. In inorder traversal, visit left subtree, then root and at last right subtree. s -> empty stack We implemented those traversals in a recursive way. // else if current node is null, we pop an element from stack, // print it and finally set current node to its right child, # Iterative function to perform in-order traversal of the tree, # start from root node (set current node to root node), # if current node is None and stack is also empty, we're done, # if current node is not None, push it to the stack (defer it). This creates a memory stack of N recursive stages before anything gets popped out. For that purpose, we have traversals for different scenarios which can be really helpful. Conflating the two meanings with a single symbol somehow blurs the mechanism a bit: Inorder traversing should give sorted nodes!! Using stack is same as a recursive algorithm. 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