Top 30+ Data Structure Interview Questions And Answers

To assist with your interview preparation, this tutorial presents frequently asked Data Structure interview questions and their answers, along with explanations.

Computer programs use data that gets converted into binary (0 and 1) and digital (positive for 1 and non-positive for 0) formats so that computers understand its value.

Developers create computer software and applications using binary data for reference or processing by a computer’s central processing unit. Developers term the method to store, organize, and efficiently use this data a data structure.

There are many ways data can be organized in memory to utilize it efficiently without occupying space or memory storage. There is a set of rules and sequences applied by a computer in computing this data, known as an algorithm.

Algorithms and Data Structures are the foundation for understanding how data is organized, stored, and optimized for efficient digital outcomes.

Expert Quiz on Data Structure Interview Questions

Try this ultimate quiz with a hand-picked list of the top Data Structure interview questions. This quiz covers all basic to advanced Data Structure concepts to boost your confidence level and crack any Data Structure interview successfully.

About Data Structure

Knowledge and skill in using Data Structures and algorithms properly help programmers and give them the ability to quickly solve complex problems most efficiently.

The algorithm is a set of instructions implemented in a computer to solve problems or for data computation. A data structure is the way a computer manages and stores data in memory to efficiently utilize it for computation.

Designers create interview questions for developers working on applications related to artificial intelligence, graphics, and operating systems to ensure efficient data management.

Beginner-Level Questions for Data Structure Interview

Q #1) Explain what a data structure is.

Answer: It is an efficient way of organizing data in order to use it effectively for retrieving and storing data in computer memory, exchanging information between applications via TCP/IN packets, ordering and sorting, memory allocation, and file directory management.

Data structures in Java are of two types: Primitive and Non-Primitive

• Primitive type contains char, int, float, double, and pointer.
• Non-Primitive type contains Array, Linked List, Stack, Queue, Tree, and Graphs.

Non-primitive Data Structure image:

Q #2) Describe what an algorithm is.

Answer: A set of rules to be followed on input data to get the desired output is called an algorithm. Programmers, mathematicians, and scientists mainly use these.

In daily life, people can apply algorithms to monitor traffic and reroute vehicles, monitor crime, track parcel deliveries, render financial data, and predict treatment procedures based on patients’ medical data.

Q #3) How do data structures and algorithms relate to each other?

Answer: Data structure is a format for organizing, managing, and storing data in an optimized manner in computer memory, whereas an algorithm is a set of rules to be followed to resolve data handling problems and retrieve the desired output. Sorting, searching, and shortest path algorithms are among the most commonly applied algorithms to data structures.

A real-life example is a recipe for a food delicacy. The algorithm will outline the steps to cook and the order in which ingredients are mixed to achieve the desired output, in this case, the desired taste.

Q #4) List various areas in which data structure is used.

Answer: Data structure can be used for storing data, data exchange, ordering, and sorting, searching, indexing, resource/ services management, and scalability in applications.

Various domain areas include:

• Artificial intelligence
• Machine Learning
• Database management
• Blockchain
• Graphics
• Simulation
• Compiler design
• Cryptography
• Statistical and Numerical Analysis
• Development of operating systems
• Processing in speech and image

Q # 5) List types of data structures with their example.

Answer: Data structure is divided into the following main categories:

• Primitive data structures in C are:
  • • char
    • pointer
    • integers
    • float
    • double
• Non-primitive data structure is further divided into Linear and Non-Linear
  • Linear
    • Array
    • Linked List
    • Stack
    • Queue
  • Non-linear
    • Tree
    • Graph

Q #6) List and describe various data structures supported in the C programming language.

Answer: The following are the data structures found in C:

• Array: Similar type elements stored sequentially in memory are known as arrays in C. They are of two types: single-dimensional and multidimensional arrays.
• Stack: It follows the last-in-first-out (LIFO) approach with a Push function to add elements and a Pop function to remove elements from a linear data structure called Stack, where both insert and delete are performed from one end of the stack.
• Queue: It is similar in structure to Stack. Queue follows the first-in-first-out (FIFO) approach, where elements are added from the back and removed from the front of the queue.
• Linked List: Unlike an array, a Linked List is not stored sequentially in memory, composed of a data section and an address section known as a node that holds the address of the next element. They are of 3 types: single link, doubly link, and circular link.
• Trees: With one root node and multiple sub-nodes designed on top of the linked list.
• Hashing: Hash table maps keys to values and is used for implementing an associative array. It uses a hash function for calculating indexes in an array of buckets.

Q #7) What are the benefits offered by the data structure?

Answer: Benefits offered are listed below:

• Storing data efficiently in storage devices.
• Convenient retrieval of data from the storage device.
• Processing small and large data effectively.
• Saves time during the storage, retrieval, or processing of data.
• Reuse and scale data using data structures like an array, tree, graph, stack, or linked list.

Q #8) Differentiate between linear and non-linear data structures.

Answer: Major differences between Linear and Non-linear data structures are listed below:

Q #9) What is an array as a data structure?

An array is a collection of elements of similar data types stored in adjacent memory locations. The lowest and highest addresses correspond to the first and the last elements of the array.

An index can access elements in the array, with 0 as an index for the first element, and the last element index is the total array size minus 1. Arrays are further divided into single and multidimensional arrays.

In Java array is declared as below:

Array myarr[] = new Array[5];

Q #10) Explain with examples – single and two-dimensional arrays.

Answer: A one-dimensional array is a data structure that stores data values of similar data types in adjacent memory blocks. In Java, number array memory for the array is allocated using the ‘new’ keyword, as defined below:

num = new int [5];

num = {2,4,6,8,10};

Data elements in the array are accessed using the index, starting with 0 as the first element’s index.

A multi-dimensional array stores multiple data elements of similar data types in a table-like format with several columns and rows.

nums = new int[2][4];

Above is a two-dimensional array of 2 rows and 4 columns.

Data Structure Scenario-Based Interview Questions

Q #11) Describe Linked List.

Answer: Linked list data structure where elements are linked using pointers, with elements not stored in adjacent memory locations. It comprises nodes, with each node containing a data field and a link referencing the next node in the list. Various operations linked list supports include insertion, deletion, display, and searching for an element using a given key.

Q #12) List the differences between arrays and linked lists.

Answer: Both arrays and linked lists belong to the linear data structure. The differences between them are listed below:

Q #13) Explain how linked lists are more efficient than arrays

Answer: The following points prove linked lists to be more efficient than arrays:

• The array size, i.e., the number of elements in an array, is fixed. Arrays need to know the upper limit of storing similar elements in advance.
• Inserting new elements in an array is expensive, as it requires shifting existing elements to create room for new elements.
• Deleting any of the existing elements from the middle of the array is expensive, as all the elements after that element need to be moved
• Linked List provides the advantage of dynamic size and ease of insertion and deletion over arrays, making it more efficient than arrays.

Q #14) Describe various scenarios where linked lists and arrays are used.

Answer: We list the scenarios explaining why a linked list or array is used.

Linked List is used:

• When it is critical to maintain the time taken for the insertion or deletion of elements.
• When the number of elements is not certain, a linked list is preferred.
• Linked List is used to store elements when random access to any element inside the list is not needed.
• When it is required to insert elements in the middle of the list, a Linked list is preferred.

Arrays are used:

• It is needed to access elements at random.
• When the number of elements is already known, arrays are preferred to allocate memory for the total number of elements.
• When iterating through all the elements, it should be quick for performance.
• When memory is of concern, an array takes less memory than a linked list.

Q #15) Explain the Doubly linked list as a data structure and its uses.

Answer: A linked list that can move back and forth in both directions is called a doubly linked list. Doubly linked lists are used when it is frequently required to find the location of the previous node. Insertion, deletion, searching, and traversal are some operations applied to a doubly linked list.

Q #16) Describe Stack as a data structure and its use.

Answer: A stack holds a linear sequence of items of an abstract data type in a particular order. It follows LIFO in inserting and removing elements.

The operations performed on Stack are:

• Push(data) – inserts data to the top of the stack,
• Peek() returns a copy of the element on the top of the stack.
• Pop – removes data from the top of the stack

Q #17) Explain Queue as a data structure and its use.

Answer: Queue is an abstract data structure that differs from Stacks as it opens at both ends, and follows FIFO (First In First Out) order when data handling operations are performed on it. One end of the Queue data structure allows insertion of data, whereas the other is used to remove data.

The queue is used when the processing of data is not immediately needed, and a resource is shared across multiple consumers.

Q #18) Explain how the stack differs from the queue?

Answer: The following are the differences between Stack and Queue:

Q #19) Describe a hash map as a data structure and its use.

Answer: A data structure known as a Hash Table stores values using a pair of keys and values. Each of these values is assigned to a unique key that is generated with a hash function. The name of the key accesses the associated value.

A Hash table or hash map implements an associative array abstract data type. Some of the uses of the hash tables include Password Verification, Pattern matching, Compiler design, file system, and creating a cryptographic message digest.

Q #20) How is collision in Java is controlled by HashMap?

Answer: The concept of Chaining is used by HashMap to handle the collision resolution in Java. Each hash code generated by the hash function is mapped to a specific bucket that contains a linked list for the case of collision. Creating a hash function that offers the best possible distribution of values throughout the hash map is the only way to avoid a collision.

Advanced Interview Questions on Data Structure

Q #21) How are variables stored in memory using data structures?

Answer:

• In a Stack data structure, variables are stored, declared, and initialized during runtime, providing temporary storage in a special area of computer memory.
• A heap is a memory space that supports dynamic memory allocation and stores global variables in computer programming languages.
• Text or code segment is a sharable single copy to be in memory for the program for frequent execution. It is read-only to prevent any accidental modification.
• The data segment is a virtual address space that contains global and static variables. It is not read-only, as variable values can be altered at run time.
• Uninitialized data segments called Block started by the symbol (BSS) are initialized by the kernel to arithmetic 0 before the program starts execution, initializing global and static variables to zero.

Q #22) Describe Priority Queue.

Answer: Priority Queue has items stored by key value as in Hash Map, such that items with the highest value of keys will be at the rear and those with the lowest value of keys will be in front.

Principal operations using Priority Queue are insert/enqueue and remove/dequeue.

• insert/enqueue inserts items at the rear of the queue.
• remove/dequeue removes an item from the front of the queue.
• peek –retrieves the element at the front of the queue.
• isFull – checks if the queue is full.
• isEmpty – verifies if the queue is empty.

Q #23) Explain Tree as a data structure and its use

Answer: A tree is a hierarchical data structure known as a collection of nodes. The tree has one node known as the root and originates from it, it has no parent. Each node represents a single parent connected to multiple edges, like children. The tree is used in predictive modeling, as it can handle large data and can be validated statistically.

Q #24) What is a binary tree in data structure?

Answer: A binary tree is a hierarchical data structure having elements with 2 children connected via a node. The structure contains Data, a Pointer to the left child, and a pointer to the right child.

In Java 8, when the number of elements in a bucket reaches a particular threshold, HashMap replaces Linked List with Binary Trees, as binary trees store at both left and right nodes, hence using more space than a singly linked list.

The binary tree structure is used to search information, manipulate hierarchical data, and sort data lists, creating router algorithms and forms that help in multi-stage decision-making.

Q #25) Explain Binary Search Tree in data structure.

Answer: Binary Search tree differs little from a binary tree in the following way:

• The left and right sub-trees (children) should also be binary search trees with no duplicate nodes.
• The node at the left sub-tree should contain nodes with keys less than the parent node key.
• The node at the right sub-tree should contain nodes with keys greater than the parent node key.

A Binary Search tree is helpful in fast lookup, addition, and removal of data items, in lookup tables, and in implementing dynamic sets.

Q #26) Describe a Graph as a data structure and its use.

Answer: A graph is a data structure where a set of interconnected objects is connected by links. The objects are called vertices, and links connecting the vertices are known as edges.

Basic operations such as Adding Vertex, Adding Edge, and displaying Vertex can be carried out in a graph structure.

Graphs are very useful in designing electrical circuit connections, the study of the algorithm, the relationship between computer networks, the molecular and chemical structure of substances such as the DNA of the organism, parsing trees of language and grammar, and connecting nodes between cities.

Q #27) List the differences between Tree and Graph.

Answer: Tree and Graph are both non-linear data structures and are collections of nodes and edges. However, the following are the differences between the two:

Q #28) Differentiate between Breadth-First Search (BFS) and Depth First Search (DFS).

Answer: The differences between BFS and DFS are listed below:

In both BFS and DFS, the Time complexity is 0(V+E), and Adjacency List used is 0(V^2) for the adjacency matrix, where V stands for Vertices and E is for Edge.

Q #29) Suggest a data structure to build a dictionary or check the spellings.

Answer: Based on memory availability and desired functionalities for spell check and dictionary, the option we have is Hashing. It is observed that hashing is efficient when it is compared with self-balancing binary search trees and skip lists.

Hashing does not support Prefix search, where the user types prefixes and the auto-suggest feature – the dictionary displays all words starting with the prefix entered. For lookup and prefix search, a Trie is appropriate, making printing words in alphabetical order possible.

However, Trie needs lots of space; here we can try the Ternary Search Tree – for the time complexity of the search operation.

Q #30) Explain how you will convert infix expression (A + B) * (C + D) into prefix expression

Answer: The following are the three steps needed to be carried out to convert the given infix expression into a prefix expression.

Step 1: Reverse the infix expression – which is (D + C) * (B + A)

The simplified form of the above expression is DC + * BA +

Step 2: Find post expression – DC + BA + * is post expression of above infix expression

Step 3: Reverse the postfix expression – Reversing the above expression we will get * + AB + CD

Hence prefix expression of infix (A + B) * (C+ D) is * + AB + CD

Q #31) How can Stack be implemented in Java using an array?

Answer: Although the Array implementation of Stack in Java is not dynamic in nature, the program is as follows:

public class Array2Stack {
        int size, arr[], top;   
    Array2Stack(int size) {
        this.size = size;
        this.arr = new int[size];
        this.top = -1;
}
public void push(int pushedElement) {
    if (!isFull()) {
    top++;
    arr[top] = pushedElement;
    System.out.println("Pushed element: " + pushedElement);
    } 
       else { 
    System.out.println("Stack is full");
     }
  }
public int pop() {
    if (!isEmpty()) {
    int returnedTop = top;
    top--;
    System.out.println("Popped element: " + arr[returnedTop]);
    }
    else {
    System.out.println("Stack is empty !");
    }
    return -1;
    }
}
public int peek() {
    if (!this.isEmpty())
    return arr[top];
    else
    {
    System.out.println("Stack is empty !");
    return -1;
    }
}
public boolean isEmpty() {
    return (top == -1);
    }
public boolean isFull() {
    return (size - 1 == top);
    }
public static void main(String [] args) {
    Array2Stack arrstk = new Array2Stack(10);
    arrstk.pop();
System.out.println("*************");
    arrstk.push(15);
    arrstk.push(25);
    arrstk.push(49);
    arrstk.push(34);
System.out.println("*************");
    arrstk.pop();
    arrstk.pop();
    arrstk.pop();
System.out.println("*************");
    }
}

The output for the above program is given below

Stack is empty!

****************

Pushed element: 15

Pushed element: 25

Pushed element: 49

Pushed element: 34

****************

Popped element: 34

Popped element: 49

Popped element: 25

**************

Conclusion

The data structure is divided into primitive data, linear data, and non-linear data. It helps to store, manipulate, and organize data to manage it effectively. Various data structure differs from one another in the way data is connected. Data processing utilizes data structures like arrays, stacks, queues, linked lists, trees, graphs, and HashMap.

For more Data Structure-related guides, you can explore our range of tutorials below:

• Introduction To Data Structures In C++
• What Are Data Structures In Python – Tutorial With Examples
• What Is A Heap Data Structure In Java
• Circular Linked List Data Structure In C++ With Illustration
• AVL Tree And Heap Data Structure In C++