Beginner to Advance: Top 21 Data Structures and AlgorithmsInterview Questions

Neha Rawat

Oct 7, 2023
Beginner to Advance: Top 21 Data Structures and Algorithms

Master data structures & algorithms with essential interview questions. From basics to advanced, learn the top 21 questions for technical success.

Data structures and algorithms are essential skills for any software engineer. They are the foundation of computer science, and they are used to solve problems in a variety of domains.

In a data structures and algorithms interview, the interviewer will ask you questions to assess your knowledge of these concepts. The questions can range from basic to advanced, so it is important to be prepared.

1. What are data structures and algorithms?

Data structures are used to make data more efficient to access and manipulate.
Algorithms are procedures for solving problems. They're used to find the most efficient way to complete a task.

2. Why are data structures and algorithms important?

  • Efficiency: Optimize program performance for faster execution.

  • Handle Lots of Stuff: They work smoothly even with lots of data or users.

  • Optimization: Identify and resolve performance issues more effectively.

  • Innovation: Contribute to creative technological advancements.

  • Reusable Code: Create modular, maintainable, and reusable code.

3. Top 21 Data Structures and Algorithms Interview Questions 

If you are interviewing for a software engineering job, you can expect to be asked data structures and algorithms questions. Here are the top 15 interview questions you must know which are in three steps:


1. What is a data structure?

Data structures are a way of organising data in a way that makes it efficient to access and manipulate.

2. What is an algorithm?

An algorithm is like a recipe for computers, guiding them step-by-step to solve problems or perform tasks.

3. What is an array?

An array is a collection of elements, such as numbers or strings, stored at contiguous memory locations. It's like a row of boxes where each box holds something different.

4. What is a linked list?

A linked list is a linear data structure where elements, called nodes, are connected through pointers, forming a sequence with dynamic size and easy insertion/removal.

5. What is a search algorithm?

A search algorithm helps find a specific item in a collection of data. It's like looking for a book on a shelf by checking each book's title.

6. What is a sorting algorithm?

A sorting algorithm arranges elements in a specific order, like arranging books on a shelf from smallest to largest based on their titles.

7. What is a stack?

A stack is a linear data structure that follows the last-in, first-out (LIFO) order.


1. Explain the time complexity of an algorithm.

Time complexity measures how an algorithm's runtime grows as the input size increases. It helps assess efficiency. Common notations include O(1), O(log n), O(n), etc.

2. What are binary trees?

A binary tree is a data structure that consists of nodes, each of which has a left child node and a right child node. This makes binary trees efficient for storing and retrieving data.

3. How do you implement a stack using an array?

Use an array with a pointer to keep track of the top element. Push adds to the top, and pop removes from the top.

4. Explain different sorting algorithms: Bubble Sort vs. Quick Sort.

Bubble Sort repeatedly steps through the list, swapping adjacent items if they're in the wrong order. Quick Sort divides the list and sorts smaller sublists.

5. What is dynamic programming?

Dynamic programming is a technique to solve problems by breaking them into overlapping subproblems, solving each subproblem only once, and storing solutions for future reference.

6. What's a hash collision, and how can it be resolved?

Hash collision is a situation in which two different inputs hash to the same value.This can be resolved by using a different hash function, or by using a collision resolution strategy such as chaining or linear probing.

7. Explain the concept of a priority queue.

A priority queue is a data structure that stores elements in a sorted order, with the highest priority element at the front. Elements are added and removed from the queue according to their priority, with the highest priority element being removed first.


1. What's the difference between a graph and a tree in data structures?

A tree is a type of graph with no cycles, while a graph is a more general structure with nodes and edges that can be cyclic.

2. Explain the A (A-star) algorithm.*

A* is a search algorithm used in pathfinding and graph traversal. It uses heuristics to estimate the cost to reach the goal, aiming for the optimal path.

3. How does the Floyd-Warshall algorithm work?

The Floyd-Warshall algorithm efficiently finds the shortest paths between all pairs of vertices in a graph by iteratively considering all possible intermediate vertices.

4. Discuss the Red-Black Tree data structure.

Red-Black Trees are balanced binary search trees with specific properties that ensure efficient operations like insertion, deletion, and search.

5. Explain the concept of amortised analysis.

Amortised analysis assesses the average time taken per operation in a data structure, considering a sequence of operations. It helps understand the overall performance.

6. Discuss the concept of Trie (Prefix Tree).

A data structure that stores data in a tree-like structure, where each node represents a prefix of a string. This makes it efficient for storing and searching for strings, especially those with common prefixes.

7. Explain the concept of graph traversal algorithms: DFS vs. BFS.

Depth-First Search (DFS) explores as far as possible along a branch before backtracking, while Breadth-First Search (BFS) explores neighbors before deeper levels. They are used to visit all nodes in a graph.

5. Conclusion

In conclusion, by exploring these top 21 data structures and algorithms interview questions from basic to advanced, you've equipped yourself with valuable knowledge for technical interviews. Keep practicing and learning to confidently tackle any coding challenge that comes your way!

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