Updated October 19, 2026
Binary tree interview questions will consist of the top 10 most important questions, which will help you crack any data structure interview. A data structure in which each node has at most two child nodes, referred to as the left child node and the right child node, and the first or top node is referred to as the root node. There are few keywords to remember in binary tree, i.e. Leaf node are the nodes which are at the bottom of the tree, which have no children. Each node in a tree has a depth, meaning the count of links from the root node. A binary tree has a height, which means the count of links from the root node to the last leaf node.
Top 10 Most Important Questions of Binary Tree
Binary tree interview questions are given below:
Q1. Define Binary Tree Data Structure?
Ans: A binary tree is a Hierarchical data structure where a tree has at most two children; i.e., a node can have either no child nodes, one child node, or two child nodes. Values of the left subtree are less than or equal to the root node, and values of the right subtree are greater than or equal to the root node.
Q2. How to find out the distance between two nodes in a binary tree?
Ans: Let us consider two nodes A and B that are part of a binary tree. The distance between Node A and Node B is the minimum number of edges required to traverse from one node to the other. NOTE: Shortest distance traversal is required in a binary tree
Q3. How to find the Lowest Common Ancestor (LCA) for a binary tree?
Ans: Let us consider two nodes N1 and N2. Lowest Common Ancestor of N1 and N2 is the shared ancestor of N1 and N2 that is located farthest from the root node
- First, we need to find the path from the root node to N1 and store it in an array
- Similarly, we need to find the path from the root node to the N2 node and store it in an array
- Then, traverse both paths until the values are equal in both arrays.
Q4. How to Check if Two Binary Trees Are Identical or Not?
Ans: To check for identical structure and content, there are two approaches: recursive approach and Iterative approach.
- In Recursive, user needs to traverse both the trees and compare values at root node. If the value matches, the user needs to check if the first tree’s left subtree is identical to the left subtree of the second binary tree and the right subtree of the first binary tree is identical to the right subtree of the second binary tree.
- If the value at the root node is different, the data property is violated.
- If at any point the first tree is empty and the second is non-empty, or the first is non-empty and the second is empty, the structural property is violated.
- In the iterative approach, a stack data structure is used, similar to the implicit recursion used in the recursive approach.
Q5. What is an AVL Tree?
Ans: AVL, named after Adelson-Velsky and Landis, who are the inventors of the AVL tree. AVL tree is a height-balanced binary tree. It checks the height of the left and right subtrees and ensures the difference is not more than 1. This difference is called the balancing factor.
- BalanceFactor(N) = height(left sub tree(N)) – height(right sub tree(N))
- N belongs to set { -1, 0, 1 }
- If the balance factor of N is more than 1, the tree is balanced using,
- Left Rotation, Right Rotation, Left-Right Rotation, Right-Right Rotation.
Q6. How is Traversing Done in a binary tree?
Ans: Traversing refers to visiting all nodes of the tree at least once. There are 3 ways in which traversing is done,
- In order
- Pre order
- Post order
Q7. What is a Binary Heap?
Ans: A binary heap is a binary tree with the following properties,
- It is a complete tree, i.e., all levels are completely filled except the last level, and has all keys as left as possible. The properties of a Binary Heap make it suitable for storage in an array.
- A binary heap has two types: a Min-Heap and a Max-Heap.
- In a Min Heap, the key at the root node must be the minimum amongst all keys present in the Binary Heap. And this property must be true for all nodes in the binary tree. Max Heap is also similar to Min Heap.
Q8. How to convert a binary tree into a binary search tree?
Ans: The main difference between a binary tree and a binary search tree is that a binary search tree follows the rule that the left subtree should have lower key values and the right subtree should have higher key values.
- This can be achieved using the following techniques,
- First, we need to create a temp array to store the in-order traversal of the binary tree.
- Then, sort the temp array using any algorithm.
- Repeat an in-order traversal.
- Finally, copy array elements to each tree node.
Q9. How to find the minimum and Maximum Element in a binary tree?
Ans: As all the elements less than or equal to given root node will be to the left, iterating the left most part of the tree will give the least element in Binary tree.
Similarly, elements greater than or equal to given root node will be to the right, iterating the right most part of the tree will give the maximum element in Binary tree.
Q10. What is the average time complexity for finding the height of a binary tree?
Ans: As the nodes are either part of the left subtree or the right subtree, the user need not traverse through all nodes, which means the complexity will be less than n. In the average case, assuming nodes are spread evenly, time complexity will be O (logn)
Conclusion
With this, we shall conclude with Binary tree interview questions. We have explored most of the important questions. Exploring more on the logical part of the binary tree data structure will help you get better at programming too. You can try to understand the concepts involved in binary trees by changing values to build the fundamentals.
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This is a guide to Binary Tree Interview Questions. Here we also discuss the introduction and the top 10 most important questions of binary trees along with explanations. You may also have a look at the following articles to learn more –
