Updated March 22, 2023
Data Structure Interview Questions and Answers
In today’s digital system, various types of data are available, and all are sometimes very structural or UN structural. Handling that type of data is very challenging at the maximum time, and there is a high risk of losing data at any time if people do not keep those data properly. A data structure is now primarily used to maintain the structure data at all times for better and more efficient use without the risk of losing critical data.
There are various kinds of data structures available in the market, and all of them follow some of their unique characteristics, so they are always a possible solution for different applications in the market. Some data structure is primarily for one or more individual tasks for their completion. For example, when designing or preparing a proper database structure (whether relational or not, it makes no difference), the organizer usually follows a B-Tree data structure.
B-Tree data structure properly provides a complete presentation of maintaining tables or the relational database structure that uses huge for any application. Now, the application cannot fulfill its requirements without this database structure. The best way for the same to use a hash table where compiler implementation is always preferable is if people are willing to identify some specific table by lookup identifier. In a top view, two kinds of data structures commonly used: Linear (Array, Stack, Queue, Linked list) and the other is Non-Linear (Trees or Graph).
Now, if you are looking for a job in Data Structure, you need to prepare for the 2023 Data Structure Interview Questions. Every interview is indeed different as per the various job profiles. Here, we have compiled relevant Interview Questions and Answers to help you succeed in your interview.
This article covers the ten most common and frequently asked Data Structure interview questions. These questions will help students build their concepts around Data Structure and help them ace the interview.
Part 1 – Data Structure Interview Questions (Basic)
This first part covers the basic Data Structure of Interview Questions and Answers.
Q1. Can you provide more details on the various actions or operations performed in data structures?
Answer: Different kinds of routine activities performed by data structure like Insertion, Deletion, Traversing, Searching, Sorting, and Merging.
- Insertion: Insertion activities for data structures include adding a new data item to a specific collection of data items.
- Deletion: The same deletion of existing data items from the defining item collection can be considered a deletion activity for the data structure.
- Traversing: Traversing means visiting the element stored in it. It serves to access each data item only once so that it can be processed. Iterating over the data structure is another name for traversing.
- Searching: Find the exact data item within a collection of data items. If a specific data item already exists in a particular data collection, we consider it a searching mechanism in data structures.
- Sorting: Maintaining the proper ordering of data items in a specific collection is now one of the most vital requirements. It always starts up proper sorting by ascending or descending data in case of a numeric data item in the collection or ordering data based on a sequence of alphabetically in case of non-numeric data.
- Merging: Merging data from two different orders in the same order may ascend or descend. Used to combine the data items from two sorted files into a single file in the sorted form.
Q2. In terms of data structures, what is the difference between a Linked List and an Array?
Answer: There is a lot of structural difference between Linked List and Array; some of the main differences are below:
- In the case of defining size, Linked Lists are always dynamic, whereas Array sizing has to initialize first.
- Inserting or deleting any data item for a collection like Linked List is very simple, whereas inserting or deleting an array of an element is too costly.
- Random access to a specific collection data item is necessary for critical kind applications. The Linked list never supports this kind of random access utility, whereas the array of elements allows random access to a specific data item.
- In memory utilization, the linked list always needed certain extra spaces for a specific pointer considering each element append inside the linked list. However, an array is typically allocated constant memory space based on the size specified at the time of initialization but also can consider whether that memory has been used at any time by the application.
Let us proceed to follow Data Structure Interview, Questions, and Answers.
Q3.Define stack, and how does it work with the application?
Answer: A stack is a well-known example of a linear data structure. It usually followed one of the most popular data structures, like maintaining order based on first in first out (FIFO) or last in last out (LILO) utility. Stack usually follows some operation, such as Pop, Push, or Peek.
The applications that stack can perform are as follows:
- Expression Evaluation: The given expression evaluates using a stack data structure. In expression evaluation by the stack is too popular in the case of postfix.
- Expression Conversion: The most important application of stacks is to convert one form of expression to another. Using stack conversion from Infix to Postfix is very easy.
- Parentheses Checking: Given an expression, determine whether or not the parenthesis correctly matched.
- Reverse Data: To reverse a given data set, we need to reorder the data so that the first and last elements exchange, then the second and second last elements, and so on. A stack is eventually helpful in case of reversing a string.
- Backtracking Problems: Backtracking is an optimization problem-solving recursive algorithm mechanism.
Q4. What is the main difference between a queue and a stack and what is a queue, and in what ways are done to implement?
Answer: A queue is a famous example of a sequence that properly follows a first in, first out order. It uses four basic operations: front, enqueue, dequeue, and rear.
The main difference between stack and queue highlighted everywhere is stack follows the Last In, First Out (LIFO) principle. It means that the most recently inserted element delete first. While in a queue, follows the principle of First In, First Out (FIFO). This means the list removes the first element added before any other element. Both can easily integrate by using arrays and linked lists.
There are two ways to implement a queue:
- Sequential allocation: It implements with an array. A queue implemented with an array organizes a limited number of elements.
- Linked list allocation: A linked list use to implement it. A queue built with a linked list can store an infinite number of elements.
Q5. What are infix, prefix, and postfix notations?
Answer:
Infix Notation:
A*(B+C)/D
Postfix Notation:
ABC+*D/
Prefix Notation:
/*A+BCD
Part 2 – Data Structure Interview Questions (Advanced)
Let us now examine the advanced Data Structure of Interview Questions And Answers.
Q6. What is a Linked List, and what are the various types available in Linked List?
Answer: Linked List: A Linked List is a collection of nodes that store randomly in memory and has two data fields: data stored at that address and a pointer to the next node in memory, and the final node pointer contains a null. There are four types, Singly Linked List, Doubly Linked List, Circular Linked List, and Circular doubly linked lists.
- Singly Linked List: A singly linked list is unidirectional and can only traverse in one direction, from the head node to the tail node.
- Doubly Linked List: A doubly linked list is bidirectional and can only traverse in both directions.
- Circular Linked List: The circular linked list is in which all nodes form a circle, and a loop is formed by connecting the first and last nodes of a circular linked list. Finally, there is no NULL.
- Circular doubly Linked Lists: A circular doubly linked list combines a doubly linked list and a circular linked list. Like the doubly linked list, it has an extra pointer called the previous pointer, and, like the circular linked list, its last node points to the head node.
Q7. What details of the data structure indicate a generation of a graph using BFS and DFS?
Answer: The queue for BFS and Stack for DFS.
- BFS(Breadth-First Search): BFS is a graph traversal algorithm that begins at the root node and explores all neighboring nodes. Then it chooses the closest node and explores all unknown nodes. Any node in the graph is regarded as the root node when using BFS for traversal.
- DFS(Depth-First Search): A recursive algorithm that searches all of the vertices of a tree data structure or graph. The algorithm begins with the first node of graph G and proceeds deeper until we reach the goal node or node with no children.
Let us proceed with Data Structure Interview, Questions, and Answers.
Q8.Which sorting algorithm is assumed to be the fastest?
A single sorting algorithm can’t be best because each algorithm develops for a specific data structure and set of data. However, most people consider the QuickSort algorithm the fastest because it performs well for most inputs. Efficient even in worst-case input sets since the order is generally random. Simple adaptation to pre-sorted or mostly-sorted inputs.
Q9. How many queues are required to provide a proper mechanism to implement a stack in the data structure?
Answer: Two Queues can implement a stack. Enqueue and dequeue operations support a queue. We must create push and pop operations using these operations.
- Push(): Push inserts a value into the stack.
- Pop(): Pop the last inserted element from the stack.
Q10. What is the LRU cache, and what are the details of which is suitable?
Answer: Queue and Hash data structures are suited to implement the LRU cache. In the case of the queue, a doubly linked list needs to implement for proper LRU cache design. In the LRU cache scheme, we can maintain the key-value pair of the hash page number and the address of the corresponding queue node to keep track of the cache.
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