Commonly Asked Interview Questions on Tree
Last Updated :
23 Jul, 2025
A tree is a hierarchical data structure consisting of nodes, with each node having a value and references (or pointers) to its child nodes. The tree structure is used to represent relationships in various domains such as file systems, organizational structures, and decision trees. One of the primary advantages of trees over arrays or linked lists is their ability to represent hierarchical relationships in a way that allows for efficient searching, insertion, and deletion operations.
Top Coding Interview Questions on Array
The following list of 50 coding problems Tree that covers a range of difficulty levels, from easy to hard, to help candidates prepare for interviews.
Top 50 Coding Problems for Interviews on Tree
Theoretical Questions for Interviews on Tree
1. What is a Tree?
A tree is a non-linear data structure consisting of nodes connected by edges. Each node contains data and references to its child nodes. It has one special node called the root, with no parent, and leaf nodes with no children.
2. What are the components of a tree?
The primary components of a tree are:
- Root: The top node in the tree, with no parent.
- Node: A basic unit of the tree, containing a value and references to its children.
- Edge: A connection between two nodes.
- Leaf: A node with no children.
- Internal node: A node with at least one child.
- Subtree: A tree that consists of a node and all its descendants.
3. What are the basic operations performed on a tree?
- Insertion: Add a new node to the tree while maintaining its properties (e.g., ordering in search trees).
- Deletion: Remove a node from the tree while preserving its structure.
- Traversal: Visit each node in the tree exactly once in a specific order (preorder, inorder, postorder).
- Searching: Find a specific node with a given value based on search criteria.
4. How would you delete a node in a binary search tree (BST)?
To delete a node in a BST, you need to handle three cases:
- Node has no children: Simply remove the node.
- Node has one child: Replace the node with its child.
- Node has two children: Find the in-order successor (the smallest node in the right subtree) or the in-order predecessor (the largest node in the left subtree) and replace the node to be deleted with the in-order successor or predecessor.
5. Explain different types of trees
- Binary Tree: Each node has at most two children (left and right).
- Full Binary Tree: Every node except leaves has two children.
- Complete Binary Tree: All levels are filled except possibly the last, and nodes are filled left to right.
- Perfect Binary Tree: Every node has two children, and all leaves are at the same level.
- AVL Tree: Self-balancing binary search tree with a height difference of at most 1 between subtrees.
- Red-Black Tree: Self-balancing binary search tree with specific coloring rules to maintain balance.
- B-Tree: Generalization of a binary search tree with more than two children per node.
- Binary Search Tree: A binary tree where the left subtree contains nodes with values smaller than the root, and the right subtree contains nodes with values greater than the root.
6. What is the difference betweeen balanced binary tree and complete binary tree?
A balanced binary tree is one where the height difference between the left and right subtrees of every node is at most 1. Balanced trees ensure that the operations such as searching, insertion, and deletion can be performed efficiently in O(log n) time. where as a complete binary tree is a binary tree in which every level, except possibly the last, is completely filled, and all nodes are as far left as possible.
7. How would you check if a binary tree is balanced?
A binary tree is balanced if, for every node, the height difference between the left and right subtrees is at most 1. This can be checked using a recursive approach, where for each node, we compute the height of its subtrees and check the balance condition.
8. What are the different ways to represent a tree in memory?
- Node-based representation. Each node stores its data and references to child nodes.
- Array-based representation. Use an array to store node data with calculations to find child nodes based on their positions.
9. What are the advantages and disadvantages of using trees?
Advantages.
- Efficient for hierarchical data representation and organization.
- Fast searching and traversal in balanced trees.
Disadvantages.
- Memory overhead due to storing pointers or references.
- Not efficient for storing large amounts of unstructured data.
10. When would you choose a tree over other data structures like arrays or linked lists?
Trees are ideal for hierarchical data, maintaining relationships between elements, and efficient searching based on order. Arrays or linked lists are better for simple linear data or frequent insertions/deletions at specific positions.
11. Explain the concept of a binary search tree.
A binary search tree has a specific ordering property. the data in the left subtree is less than the root, and the data in the right subtree is greater than the root. This allows for efficient searching by comparing values with the root and navigating left or right accordingly.
12. How do self-balancing trees like AVL or Red-Black trees work?
These trees automatically adjust their structure after insertions or deletions to maintain a balanced height, ensuring efficient search and insertion/deletion operations. They achieve this through specific rules and rotations based on node heights and colors.
13. Describe the different tree traversal methods (preorder, inorder, postorder).
- Preorder. Visit root, then left subtree, then right subtree.
- Inorder. Visit left subtree, then root, then right subtree.
- Postorder. Visit left subtree, then right subtree, then root.
Each traversal method has different purposes. Inorder is useful for printing sorted elements in a binary search tree, while preorder might be used for copying tree structure.
14. How would you find the minimum and maximum elements in a binary search tree (BST)?
To find the minimum element in a BST, you need to keep traversing the left child until you reach the leftmost leaf. For the maximum element, you keep traversing the right child until you reach the rightmost leaf.
15. How can you convert a binary search tree into a sorted array?
One efficient way is to use an inorder traversal of the tree. Since the tree is sorted, visiting nodes in this order will result in a sorted array.
16. Explain the concept of a minimum spanning tree.
A minimum spanning tree is a subgraph of a connected, undirected graph that includes all vertices but with the minimum total edge weight, connecting all nodes without cycles. It has applications in network routing and clustering algorithms.
17. What is a trie?
A trie is a special type of tree used to store a dynamic set of strings, where each node represents a character of the string. Tries are commonly used for implementing autocomplete and dictionary-based applications.
12. Describe the use cases of trees in real-world scenarios.
Trees are used in various domains, including:
- File systems (directory structure)
- XML or JSON data representation
- Decision trees for machine learning
- Game AI (representing game states and possible actions)
- Social networks (representing user relationships)
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