Top Data Structure Interview Questions and Answers for Freshers (2025 Guide)
Data Structures are one of the most important topics in computer science interviews. Every beginner in programming must have a good understanding of them because they form the base for solving problems efficiently.
In this article, we’ll go through the most commonly asked data structure interview questions with simple and easy-to-understand answers that will help you prepare confidently.
1. What is a Data Structure?
A data structure is a way of organizing and storing data so that we can use it efficiently.
For example, if we want to store a list of names, we can use an array or a linked list.
Example:
Imagine a shelf where you keep your books in order. That shelf is like a data structure—it helps you organize data (books) properly.
2. What are the types of Data Structures?
Data structures are mainly divided into two types:
- Linear Data Structures – Data elements are arranged in a sequence.
Examples: Array, Linked List, Stack, Queue - Non-Linear Data Structures – Data elements are connected in a hierarchy.
Examples: Tree, Graph
3. What is the difference between an Array and a Linked List?
| Feature | Array | Linked List |
|---|---|---|
| Memory Allocation | Fixed size | Dynamic size |
| Insertion/Deletion | Difficult | Easy |
| Access Time | Fast (direct access) | Slow (sequential access) |
| Memory Usage | May waste space | Efficient use of memory |
Example:
If you know the number of elements in advance, use an array.
If the size keeps changing, use a linked list.
4. What is a Stack?
A stack is a linear data structure that follows the LIFO (Last In, First Out) principle.
It means the last element added is the first one removed.
Example:
Think of a pile of plates—You can only take the top plate first.
Common operations:
- push() → Add element
- pop() → Remove element
- peek() → View top element
5. What is a Queue?
A queue is a linear data structure that follows the FIFO (First In, First Out) principle.
The first element added is the first one removed.
Example:
People standing in a line at a ticket counter – the first person in line gets the ticket first.
Common operations:
- enqueue() → Add element
- dequeue() → Remove element
6. What is a Linked List?
A linked list is a collection of nodes where each node contains two parts:
- Data
- Pointer (link) to the next node
Types of Linked Lists:
- Singly Linked List
- Doubly Linked List
- Circular Linked List
Example:
A train where each compartment is connected to the next one.
7. What is a Binary Tree?
A binary tree is a tree data structure where each node has at most two children—left and right.
Example:
10
/ \
20 30
Common types of binary trees:
- Full Binary Tree
- Complete Binary Tree
- Binary Search Tree (BST)
8. What is a Binary Search Tree (BST)?
A Binary Search Tree is a special kind of binary tree where:
- Left child < Parent node
- Right child > Parent node
Example:
8
/ \
3 10
/ \ \
1 6 14
Use: Searching and sorting data efficiently.
9. What is a Hash Table?
A hash table stores data in key-value pairs. It uses a hash function to convert a key into an index in an array.
Example:
If you want to quickly find a student’s record by ID, a hash table helps you find it in O(1) time.
10. What is the difference between Stack and Queue?
| Feature | Stack | Queue |
|---|---|---|
| Principle | LIFO (Last In, First Out) | FIFO (First In, First Out) |
| Example | Stack of books | Line at a bus stop |
| Operations | push, pop | enqueue, dequeue |
11. What is a Graph?
A graph is a non-linear data structure that consists of nodes (vertices) connected by edges.
Types of Graphs:
- Directed Graph
- Undirected Graph
- Weighted Graph
Example:
A map showing cities connected by roads.
12. What is Recursion in Data Structures?
Recursion is when a function calls itself to solve a smaller version of the same problem.
Example:
Factorial of n = n × factorial(n-1)
13. What is the difference between Linear and Non-Linear Data Structures?
| Type | Example | Structure |
|---|---|---|
| Linear | Array, Stack, Queue | Data arranged sequentially |
| Non-Linear | Tree, Graph | Data connected in a hierarchy |
14. What is a Heap?
A heap is a special tree-based data structure that satisfies the heap property:
- In a max heap, parent node > child nodes
- In a min heap, parent node < child nodes
Use: In priority queues and heap sort.
15. What is the difference between a Tree and a Graph?
| Feature | Tree | Graph |
|---|---|---|
| Structure | Hierarchical | Network |
| Cycles | No cycles | May have cycles |
| Connection | One root node | Multiple connections |
16. What is a Circular Linked List?
In a circular linked list, the last node points back to the first node, forming a circle.
Example:
Used in playlist apps where songs repeat after the last one.
17. What are the applications of Data Structures?
Data structures are used everywhere in programming:
- Arrays: Storing lists
- Stacks: Undo operation
- Queues: Task scheduling
- Trees: File systems
- Graphs: Social networks
- Hash tables: Databases and caches
18. What is the difference between Time Complexity and Space Complexity?
- Time Complexity: How much time a program takes to run.
- Space Complexity: How much memory a program uses.
Example:
If an algorithm takes 10 steps for input size 5, the time complexity is O(n).
19. What is Dynamic Memory Allocation?
It means allocating memory during program runtime using functions like malloc(), calloc(), and free() in C.
This is useful when we don’t know the size of data in advance.
20. What are Common Operations on Data Structures?
- Insertion – Add a new element
- Deletion – Remove an element
- Traversal – Visit each element
- Searching – Find an element
- Sorting – Arrange elements in order
21. What is Depth-First Search (DFS) and Breadth-First Search (BFS)?
Both are graph traversal methods:
- DFS: Explore as far as possible before backtracking (uses stack).
- BFS: Visit neighbors first before moving deeper (uses queue).
22. What is a Priority Queue?
A priority queue is a queue where each element has a priority, and elements with higher priority are served first.
Example:
In hospitals, emergency patients are treated before others.
23. Why are Data Structures Important?
They help in:
- Storing data efficiently
- Fast searching and sorting
- Reducing memory usage
- Writing clean and optimized code
Conclusion
Data structures are the foundation of computer programming. Understanding how each one works and when to use it will make you a better programmer and problem solver.
As a fresher, focus on learning the basic structures like arrays, stacks, queues, linked lists, trees, and graphs with small examples in your favorite programming language (like Python, Java, or C++).