Infosys Data Structure Technical Interview Questions and Answers
When preparing for a technical interview at Infosys, one of the most important areas to master is Data Structures. This is because data structures form the backbone of efficient programming — they determine how data is stored, accessed, and manipulated.
In Infosys interviews, questions on data structures are designed to test not just your theoretical knowledge, but also your ability to analyze problems and implement optimized solutions. Based on common patterns, here’s a detailed set of Infosys Data Structure interview questions and answers that can help you prepare effectively.
1. Basic Data Structure Questions
Q1. What is a data structure? Why is it important?
A data structure is a way of organizing and storing data so that it can be used efficiently. It is important because the right choice of data structure can improve the performance of algorithms, reduce memory usage, and solve problems effectively.
Q2. What are the different types of data structures?
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Linear Data Structures: Arrays, Linked Lists, Stacks, Queues.
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Non-linear Data Structures: Trees, Graphs, Heaps.
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Hash-based Structures: Hash Tables, Hash Maps.
Q3. What is the difference between an array and a linked list?
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Array: Fixed size, random access using index, contiguous memory.
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Linked List: Dynamic size, sequential access, nodes connected using pointers.
Q4. What is a stack? Give a real-world example.
A stack is a LIFO (Last In, First Out) data structure.
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Operations: Push (insert), Pop (remove), Peek (top element).
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Example: Undo functionality in text editors.
Q5. What is a queue? How is it different from a stack?
A queue is a FIFO (First In, First Out) data structure.
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Example: Ticket booking system.
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Stack removes the last inserted element, while queue removes the first inserted element.
2. Intermediate Data Structure Questions
Q6. What are different types of linked lists?
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Singly Linked List → Nodes connected in one direction.
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Doubly Linked List → Nodes connected in both directions.
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Circular Linked List → Last node points back to the first.
Q7. What is the difference between stack and heap memory?
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Stack Memory: Stores local variables and function calls, managed automatically.
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Heap Memory: Stores dynamic data, managed manually by programmer.
Q8. What is a binary search tree (BST)?
A tree where each node has at most two children:
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Left child < Parent node
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Right child > Parent node
BST allows efficient searching, insertion, and deletion in O(log n) time on average.
Q9. What is the difference between BFS and DFS in graphs?
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BFS (Breadth-First Search): Uses a queue, explores level by level.
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DFS (Depth-First Search): Uses a stack/recursion, explores depth before backtracking.
Q10. Explain hash tables. Why are they efficient?
Hash tables use a hash function to map keys to indices in an array. They provide O(1) average time complexity for insertion, deletion, and search. Collisions are handled using chaining or open addressing.
3. Advanced Data Structure Questions
Q11. What is a heap? Where is it used?
A heap is a special tree-based structure that satisfies the heap property.
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Max Heap: Parent is greater than children.
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Min Heap: Parent is smaller than children.
Heaps are widely used in priority queues and heap sort algorithms.
Q12. What is dynamic programming and how is it related to data structures?
Dynamic programming is an optimization technique that stores intermediate results in arrays, hash tables, or trees to avoid redundant calculations. Many DP problems depend on efficient data structure usage.
Q13. Explain trie data structure.
A trie is a tree-like structure used for storing strings, where each node represents a character.
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Efficient for prefix-based searching (e.g., auto-suggestions in search engines).
Q14. How do you detect a cycle in a linked list?
Using Floyd’s Cycle Detection Algorithm (Tortoise and Hare):
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Move one pointer one step and the other two steps.
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If they meet, a cycle exists.
Q15. How do you implement a stack using queues?
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Use two queues. Push operation is costly (insert and rearrange), while pop is efficient.
This is a classic Infosys interview question that tests problem-solving skills.
4. Real-World Problem-Solving Questions
Q16. Reverse a linked list.
This is a common coding challenge. Approach: Iteratively change next pointers or use recursion.
Q17. Find the middle element of a linked list in one traversal.
Use two pointers: one moves one step, the other moves two steps. When the fast pointer reaches the end, the slow pointer will be at the middle.
Q18. Implement a queue using stacks.
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Use two stacks. For enqueue, push to stack1. For dequeue, transfer elements to stack2, pop one, then move back.
Q19. Find the first non-repeating character in a string.
Use a hash table to count frequencies, then scan to find the first character with frequency 1.
Q20. How do you check if a binary tree is balanced?
Use recursion: check if left and right subtrees differ in height by at most one and are themselves balanced.
Final Thoughts
Infosys data structure interview questions are not about memorizing definitions but about showing logical thinking, efficiency, and clarity of approach. The panel often gives small variations of standard problems (like reversing a list or finding duplicates) to see if you can adapt your knowledge.
If you’re preparing for Infosys, my suggestion is:
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Revise the fundamentals (arrays, linked lists, stacks, queues).
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Practice tree and graph problems.
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Focus on real-world coding problems like searching, sorting, and string handling.
With consistent practice, you’ll be ready to handle any data structure problem Infosys throws at you.