Binary TreesBinary Trees36
  1. 1Preorder Traversal of a Binary Tree using Recursion
  2. 2Preorder Traversal of a Binary Tree using Iteration
  3. 3Inorder Traversal of a Binary Tree using Recursion
  4. 4Inorder Traversal of a Binary Tree using Iteration
  5. 5Postorder Traversal of a Binary Tree Using Recursion
  6. 6Postorder Traversal of a Binary Tree using Iteration
  7. 7Level Order Traversal of a Binary Tree using Recursion
  8. 8Level Order Traversal of a Binary Tree using Iteration
  9. 9Reverse Level Order Traversal of a Binary Tree using Iteration
  10. 10Reverse Level Order Traversal of a Binary Tree using Recursion
  11. 11Find Height of a Binary Tree
  12. 12Find Diameter of a Binary Tree
  13. 13Find Mirror of a Binary Tree
  14. 14Left View of a Binary Tree
  15. 15Right View of a Binary Tree
  16. 16Top View of a Binary Tree
  17. 17Bottom View of a Binary Tree
  18. 18Zigzag Traversal of a Binary Tree
  19. 19Check if a Binary Tree is Balanced
  20. 20Diagonal Traversal of a Binary Tree
  21. 21Boundary Traversal of a Binary Tree
  22. 22Construct a Binary Tree from a String with Bracket Representation
  23. 23Convert a Binary Tree into a Doubly Linked List
  24. 24Convert a Binary Tree into a Sum Tree
  25. 25Find Minimum Swaps Required to Convert a Binary Tree into a BST
  26. 26Check if a Binary Tree is a Sum Tree
  27. 27Check if All Leaf Nodes are at the Same Level in a Binary Tree
  28. 28Lowest Common Ancestor (LCA) in a Binary Tree
  29. 29Solve the Tree Isomorphism Problem
  30. 30Check if a Binary Tree Contains Duplicate Subtrees of Size 2 or More
  31. 31Check if Two Binary Trees are Mirror Images
  32. 32Calculate the Sum of Nodes on the Longest Path from Root to Leaf in a Binary Tree
  33. 33Print All Paths in a Binary Tree with a Given Sum
  34. 34Find the Distance Between Two Nodes in a Binary Tree
  35. 35Find the kth Ancestor of a Node in a Binary Tree
  36. 36Find All Duplicate Subtrees in a Binary Tree
GraphsGraphs46
  1. 1Breadth-First Search in Graphs
  2. 2Depth-First Search in Graphs
  3. 3Number of Provinces in an Undirected Graph
  4. 4Connected Components in a Matrix
  5. 5Rotten Oranges Problem - BFS in Matrix
  6. 6Flood Fill Algorithm - Graph Based
  7. 7Detect Cycle in an Undirected Graph using DFS
  8. 8Detect Cycle in an Undirected Graph using BFS
  9. 9Distance of Nearest Cell Having 1 - Grid BFS
  10. 10Surrounded Regions in Matrix using Graph Traversal
  11. 11Number of Enclaves in Grid
  12. 12Word Ladder - Shortest Transformation using Graph
  13. 13Word Ladder II - All Shortest Transformation Sequences
  14. 14Number of Distinct Islands using DFS
  15. 15Check if a Graph is Bipartite using DFS
  16. 16Topological Sort Using DFS
  17. 17Topological Sort using Kahn's Algorithm
  18. 18Cycle Detection in Directed Graph using BFS
  19. 19Course Schedule - Task Ordering with Prerequisites
  20. 20Course Schedule 2 - Task Ordering Using Topological Sort
  21. 21Find Eventual Safe States in a Directed Graph
  22. 22Alien Dictionary Character Order
  23. 23Shortest Path in Undirected Graph with Unit Distance
  24. 24Shortest Path in DAG using Topological Sort
  25. 25Dijkstra's Algorithm Using Set - Shortest Path in Graph
  26. 26Dijkstra’s Algorithm Using Priority Queue
  27. 27Shortest Distance in a Binary Maze using BFS
  28. 28Path With Minimum Effort in Grid using Graphs
  29. 29Cheapest Flights Within K Stops - Graph Problem
  30. 30Number of Ways to Reach Destination in Shortest Time - Graph Problem
  31. 31Minimum Multiplications to Reach End - Graph BFS
  32. 32Bellman-Ford Algorithm for Shortest Paths
  33. 33Floyd Warshall Algorithm for All-Pairs Shortest Path
  34. 34Find the City With the Fewest Reachable Neighbours
  35. 35Minimum Spanning Tree in Graphs
  36. 36Prim's Algorithm for Minimum Spanning Tree
  37. 37Disjoint Set (Union-Find) with Union by Rank and Path Compression
  38. 38Kruskal's Algorithm - Minimum Spanning Tree
  39. 39Minimum Operations to Make Network Connected
  40. 40Most Stones Removed with Same Row or Column
  41. 41Accounts Merge Problem using Disjoint Set Union
  42. 42Number of Islands II - Online Queries using DSU
  43. 43Making a Large Island Using DSU
  44. 44Bridges in Graph using Tarjan's Algorithm
  45. 45Articulation Points in Graphs
  46. 46Strongly Connected Components using Kosaraju's Algorithm

Zigzag Traversal of a Binary Tree - Iterative Approach

Problem Statement

Given a binary tree, perform a zigzag (also called spiral order) traversal using an iterative approach. In zigzag traversal, the nodes of the binary tree are printed level by level, but the direction alternates — the first level is printed left to right, the second level right to left, the third left to right again, and so on. The task is to return a list of values representing this traversal order.

Examples

Input Tree Zigzag Traversal Output Description
[1, 2, 3, 4, 5, null, 6]
[[1], [3, 2], [4, 5, 6]] Standard tree with three levels, showcasing left-to-right and right-to-left alternation
[1]
[[1]] Edge case: Single-node tree (root only)
[] [] Edge case: Empty tree with no nodes
[1, 2, null, 3, null, null, null, 4]
[[1], [2], [3], [4]] Left-skewed tree; no right branches, still follows zigzag pattern per level
[1, null, 2, null, null, null, 3]
[[1], [2], [3]] Right-skewed tree; no left branches, still alternates direction at each level
[7, 9, 8, 1, 5, 3, 6]
[[7], [8, 9], [1, 5, 3, 6]] Balanced tree with full left and right subtrees to demonstrate alternating level order

Visualization Player

Solution

Case 1: Empty Tree

If the binary tree is empty (i.e., root is null), then there's nothing to traverse. So, the expected output is simply an empty list. This is the base case and should be handled first in your solution logic to avoid errors.

Case 2: Single Node Tree

If the tree contains only a root node and no children, the zigzag traversal is just the root itself. This is straightforward since there’s only one level and hence no alternating direction needed.

Case 3: Full Tree with Multiple Levels

This is the most common scenario where the tree has multiple levels and child nodes. The traversal begins at the root level (left to right), then flips direction for the next level (right to left), and so on. To implement this iteratively, two stacks are used: one for the current level and one for the next. Depending on the direction, we push children in different orders — left then right if going left-to-right, or right then left if going right-to-left.

Case 4: Left-Skewed Tree

In a left-skewed tree, each node has only a left child. Although we still alternate direction, each level contains only one node, so the order of printing doesn’t change. The result is simply the nodes from top to bottom.

Case 5: Right-Skewed Tree

Similarly, in a right-skewed tree where each node has only a right child, the zigzag traversal becomes identical to a top-to-bottom traversal since each level contains just one node. Direction toggling has no visible impact here as well.

By using two stacks and carefully managing the traversal direction, this iterative solution efficiently captures the zigzag pattern and works for all types of binary trees — balanced, skewed, or even empty.

Algorithm Steps

  1. If the binary tree is empty, return an empty result.
  2. Initialize two stacks: currentStack and nextStack. Push the root node onto currentStack.
  3. Set a boolean flag leftToRight to true to indicate the traversal direction.
  4. While currentStack is not empty, do the following:
    1. Initialize an empty list to store the values of the current level.
    2. While currentStack is not empty, pop a node from it and record its value.
    3. If leftToRight is true, push the node's left child then right child (if they exist) onto nextStack; otherwise, push the node's right child then left child onto nextStack.
    4. After processing the current level, add the recorded values to the result.
    5. Swap currentStack with nextStack and toggle the leftToRight flag.
  5. Continue until all levels have been processed; the collected values form the zigzag traversal of the binary tree.

Code

Python
Java
JavaScript
C
C++
C#
Go
class TreeNode:
    def __init__(self, val=0, left=None, right=None):
        self.val = val
        self.left = left
        self.right = right

def zigzagTraversal(root):
    if not root:
        return []
    result = []
    currentStack = [root]
    nextStack = []
    leftToRight = True
    level = []
    while currentStack:
        node = currentStack.pop()
        level.append(node.val)
        if leftToRight:
            if node.left:
                nextStack.append(node.left)
            if node.right:
                nextStack.append(node.right)
        else:
            if node.right:
                nextStack.append(node.right)
            if node.left:
                nextStack.append(node.left)
        if not currentStack:
            result.append(level)
            level = []
            currentStack, nextStack = nextStack, []
            leftToRight = not leftToRight
    return result

# Example usage:
if __name__ == '__main__':
    # Construct binary tree:
    #         1
    #        / \
    #       2   3
    #      / \   
    #     4   5  
    root = TreeNode(1, TreeNode(2, TreeNode(4), TreeNode(5)), TreeNode(3))
    print(zigzagTraversal(root))