Most Common DSA Interview Questions
Data Structures and Algorithms assist us in solving programming issues. They simplify working with data and identifying intelligent solutions. DSA questions are frequently required in company job interviews, particularly for data science or Java positions. The following questions can assist you in preparing and performing well in your next interview!
DSA Interview Questions for Freshers
1. What is a Data Structure?
Data structure is a way of storing and organizing data so that we can easily retrieve it. It also assists in connecting various parts of data and creating steps (algorithms) to solve problems.
2. What are the types of Data Structures?
Some of them are common:
• Lists: A sequence of items in which each item is relevant to the preceding or succeeding item.
• Arrays: A collection of items that are all of the same type, like numbers or letters.
• Records: A collection of fields, such as a form with fields for name, age, and address.
• Trees: A way to organize data in layers, like a family tree. It shows how data is inserted, removed, or updated.
• Tables: Facts are stored in rows and columns, similar to a spreadsheet. Altering one element can alter the entire table.
3. What is a Linear Data Structure? Provide some examples?
A linear data structure holds the items in line or order. Every item, other than the first and the last, has one item before it and one item following it.
Examples are Arrays, Linked Lists, Queues, and Stacks.
4. What are the uses of Data Structures?
This is a frequent interview question in job interviews.
Data structures find use in many areas including:
• Numerical analysis (math problem solving)
• Operating systems
• Artificial Intelligence (AI)
• Compilers' creation
• Managing databases
• Graphics and animation
• Statistics
• Models and simulations
5. What is the difference between file structure and storage structure?
The distinction lies in where the data is located.
• The storage type is within the main computer memory (RAM).
• Structure of files is in the computer's additional memory (such as hard drives or USBs).
6. What is a multidimensional array?
A multidimensional array is similar to a box with boxes of data within it.
The easiest one is a 2D array, which is similar to a table with rows and columns.
It is a list of lists. It is also called a matrix.
7. Where are the elements of a 2D array stored in memory?
There are two options:
• Row-Major Order: The elements of the first row are stored first. Then, the second row is stored, and so on.
• Column-Major Order: The elements of the first column are stored first, followed by the second column, and so on.
8. What is a Linked List?
This is a truly significant interview question! A linked list is a method of storing data along a line, similar to a chain. However, the objects are not stored side by side in memory.
Each thing (known as a node) has two components:
One part stores the information.
• The other part points to the next node
The first node is called the head. The head is null if the list is empty. The last node also points to null.
Why use a linked list?
• You may not know how much you have to store.
• You must insert or remove items quickly
• You do not need to pick any product blindly.
You want to place things in the middle.
• Applied in stacks, queues, graphs, directories, and performing arithmetic operations with large numbers
9. Linked Lists, Linear or Non-Linear Data Structures?
Linked lists may be linear or non-linear — we can choose how we construct them.
• If we use them to process items one after another (e.g., reading a list), it's linear.
If we apply them to keep things in varying forms, such as graphs or trees, then it can be non-linear.
10. What are advantages of a Linked List over an Array? When Should We Use Both?
This is an interview question. Following is the explanation why arrays are superior to linked lists:
Advantages of Linked Lists:
1. Easy to Add or Remove Items
You can remove or add items without shifting everything else. In arrays, you shift lots of items to make room.
2. Flexible Size
A linked list can resize up or down as required. Arrays must have the size as you declare them.
3. No Memory Waste
Linked lists take up only the space they require. Arrays can waste space if they are not fully filled.
4. Good for Special Structures
Stacks and queues are more easily implemented in terms of linked lists.
When to Use a Linked List:
• You have no idea how many you'll require
You have to keep adding or subtracting things.
• You should not choose things randomly.
• You'd like to put things in the center, such as in a to-do list.
When to Use an Array:
• You must look for things in a hurry by position (e.g., the 3rd or 10th thing)
• You know how many you have before you need them.
You have to move quickly through the list.
• Save memory because arrays take up less memory than linked lists.
11. What is a Doubly-Linked List? Can You Give Examples?
A doubly-linked list is a unique kind of linked list. Every node (or element) has two links:
• Each link takes us to the next one.
• The second reference refers to the previous node
• This enables you to move forward and backward within the list.
Examples:
• A music playlist where you can click next or previous
• A browser which enables you to go forward or backward between the pages.
• An undo/redo button so you can go back to what you just did
12. How do you access all the elements in a one-dimensional array?
You may iterate over each element in the array using a loop.
The loop starts from 0 and goes till the end, and the nth element is at n - 1 position.
This way, you can consider each item in the array one at a time.
13. What are dynamic data structures? Can you give some examples?
Dynamic data structures can get bigger or smaller while a program is running.
This saves memory because you only use what you need.
Examples
• Linked lists
• Stacks
• Queues
• Charts
• Trees
14. What is an Algorithm?
An algorithm is a list of things you do to work out a problem.
It is like the recipe which teaches you stepwise what to follow in order to arrive at the right answer.
15. Why Do We Study Algorithms?
There are numerous ways of solving a problem.
Algorithm analysis helps us select the optimal one.
It reminds us:
• How fast the algorithm executes (this is referred to as time complexity)
• How much memory it uses (this is called space complexity)
• This helps us create better and quicker programs.
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