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Table of contents
1.
Introduction
1.1.
Important Interview Questions
2.
FAQs
2.1.
What is data abstraction?
2.2.
Why are linear data structures easy to implement?
2.3.
What is the complexity of adding an element to the heap.
2.4.
What happens to the data inserted first in a queue?
2.5.
How many stacks are needed to implement a queue?
3.
Conclusion
Last Updated: Mar 27, 2024
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Data Structure Interview Questions| Part 2

Author Aditya Anand
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12 Jun, 2024 @ 01:30 PM

Introduction

Welcome Readers! Data Structure is the most basic and essential part of Computer Programming as well as Software interviews. No doubt, this is a highly required skill in all software interviews. This series of 3 blogs will cover the most crucial data structure questions. After reading the blog, make sure to visit other blogs by visiting part1 and part3.

We hope you learn a lot from this blog.

Important Interview Questions

  1. What are dynamic Data Structures? Name a few.
    They're memory collections that expand and contract to grow or shrink in size as a programme runs. This gives the programmer complete control over how much memory is used.
    The dynamic array, linked list, stack, queue, and heap are among the examples.
     
  2. What operations can be performed on queues?
    Following are the operations that can be performed on the queue:

    → init() for initializing the queue.
    → enqueue() to add an element at the end of the queue.
    → dequeue() this removes an element from the front of the queue
    → front() to get the value of the first data item without removing it
    → rear()  to get the last item from a queue rear is used
    → isEmpty() tests for whether the queue is empty or not
     
  3. List the types of trees?
    Following are the types of trees:

    The General Tree: If a tree's hierarchy isn't restricted, it's called a generic tree. Each node in the General Tree can have an infinite number of progeny, and all other trees are subsets of it.

    The Binary Tree: A binary tree is a tree in which each parent has at least two children. Left and right youngsters are the names given to the children. This tree is more well-known than the others. Various trees such as the AVL tree, BST (Binary Search Tree), RBT tree, and others are used when particular limits and features are given to a Binary tree. 

    Binary Search Tree: BST is a binary tree extension with a lot of different limitations. The left child value of a node should be less than or equal to the parent value in BST, whereas the correct child value should always be greater than or equal to the parent's value.

    The AVL Tree: The AVL tree is a binary search tree that self-balances. The initials AVL stand for Adelson-Velshi and Landis, the two inventors. The first tree to attain dynamic equilibrium was this one. Depending on whether the AVL tree is balanced or not, each node is assigned a balancing factor. One AVL vine is the maximum height for the node kids.

    Red and Black Tree: Another sort of auto-balancing tree is the red-black tree. The word red-black comes from the characteristics of a red-black tree, which has either red or black painted on each node. It contributes to the forest's overall balance. Despite the fact that this tree isn't completely balanced, the search method only takes O (log n) time.

    The N-ary Tree: The maximum number of children in this type of tree with a node is N. Because each binary tree node has just two offspring, a binary tree is a two-year tree. A full N-ary tree is one where each node's children are either 0 or N.
     
  4. What is a queue in data structure?
    A queue is a data structure that is similar to a stack. Queue, unlike stack, has doors on both ends. The one end is always used to input data (enqueue), while the other is always used to delete data (dequeue) (dequeue). The queue follows the First-In-First-Out principle, which means that the data item that was stored first will be accessed first.

    (Source:   logicmojo)
     
  5.  How do you find the height of a tree?
    The number of edges in the longest path from the root node to the leaf equals the node's height, where the depth of a leaf node is 0.
    Check this blog to read more about finding the height of a tree.

     
  6. List the data structures which are used in RDBMS, Network Data Modal, and Hierarchical Data Model.
    Following data structures are used:

    → The hierarchal data model uses Tree.
    → RDBMS uses the Array data structure
    → The network data model uses Graph.
     
  7. What are the drawbacks of array implementation of Queue?
    Following are the drawbacks:

    → Memory Wastage: Because items can only be put at the front end, and the value of the front may be so high that all the space before that can never be filled, the array space used to store queue elements can never be reused to store queue elements.

    → Array Size: There may be occasions where we need to extend the queue to insert additional components, and if we use an array to create the queue, it will be nearly hard to do so. As a result, determining the suitable array size is always an issue in array queue implementation.

     
  8. State the properties of the B Tree.
    A B tree of order m contains all the properties of an M way tree. In addition, it contains the following properties.

    → In a B-Tree, each node has at most m children.
    → The level of all leaf nodes must be the same.
    → There must be at least two root nodes.
    → Except for the root and leaf nodes, every node in a B-Tree has at least m/2 children.

     
  9. What are the differences between B tree and B+ tree?
    Following are the difference between B and B+ trees:



     
  10. Differentiate among cycle, path, and circuit?
    Path: A path is a non-restricted sequence of consecutive vertices connected by edges.

    Cycle: A cycle is a closed path where the initial vertex and the end vertex are the same. The path's vertex cannot be visited twice.

    Circuit: A circuit is a closed path where the initial vertex and the end vertex are the same. Any vertex can be repeated multiple times.
     
  11. List Some Applications of Multilinked Structures?
    Following are the Application of Multilinked Structures:

    → Sparse matrix,
    → Index generation.
     
  12. Why do we use queues?
    Queues are used when we need to work on data items in the exact order in which they arrive, i.e. to prioritise jobs, as in the following scenarios.

    → Various processes are queued in every operating system.
    → Some instances of queues are priority queues and graph traversal by breadth-first.
    → Waiting lists for a single shared resource, such as a printer, CPU, call centre systems, or picture uploads, where the first one entered is processed first.
    → Pipes, file IO, and sockets are examples of asynchronous data transport.
    → In applications such as MP3 players and CD players, as buffers
    → To keep the playlist in media players up to date (to add or remove the songs)

     
  13. What operations can be performed on Queues?
    The below operations can be performed on a stack −

    → isempty()  checks if stack is empty
    → isfull()  checks if stack is full
    → peek()  gives the value of a front item without removing it
    → dequeue()  removes the item from the front of the queue
    → enqueue()  adds an item to the rear of the queue
     
  14. What is Hashmap Data Structure and Hashing?

    Hashmap is a data structure that implements the hash table data structure, allowing you to access data in constant time (O(1)), assuming you know the key.
    If the hash function employed in the hash map distributes elements uniformly among the buckets, the time complexity is O(1).
    The item that was most recently added to a stack is removed first. In the event of a queue, the item that was most recently added gets removed first.
    Hashing is a method of converting a set of key values into a set of array indexes. We can establish an associative data storage using hash tables, where data indexes can be found by supplying their key values

    .
  15. Enumerate the various operations that can be performed on a data structure?
    Following are the various operations that can be performed on a data structure:

    → Deletion: removing an existing data structure element.
    → Insertion: it is the process of adding a new element to a data structure.
    → Searching: Find the position of an element in the data structure if it exists.
    → Sorting: Arranging data structure elements in.
    → Traversal: Processing each element of a data structure just once.
     
  16. In what ways are Linked Lists better than arrays?



     
  17. Explain the scenarios where you can use linked lists and arrays?
    Following are the scenarios where we use a linked list over an array:

    → There are fewer random access operations.
    → A linked list is better for inserting items anywhere in the middle of a list, such as when building a priority queue.
    → When we don't know how many elements there will be ahead of time.
    → The following are examples of when we utilise arrays instead of linked lists:
    → When we need to iterate over the sequence's elements quickly.
    → When we need to index or access elements at random more often.
    → Because of the differences between arrays and linked lists, it's safe to assume that filled arrays consume less memory than linked lists.
    → In a word, while picking which data structure to utilise over what, space, time, and ease of implementation are all taken into account.

     
  18. What is a doubly-linked list (DLL)? What are its applications?
    It's a special sort of linked list (double-ended LL) in which each node has two links, one to the next node in the sequence and the other to the previous node. This permits traversal in both directions across the data pieces.


    Applications: 

    → BACK-FORWARD viewed pages in the browser cache
    → On systems like Word and Paint, you can reverse the node to return to the previous page using the undo and redo capability.

     
  19. What is a heap data structure?
    Heap is a non-linear data structure built on a tree with a complete binary tree as the tree. A binary tree is said to be full if all levels are completely filled, with the exception of the last level, which has all items pointing to the left. 

    There are two types of heaps:
    → The data element at the root node of a Max-Heap must be the greatest of all the data elements in the tree.
    → The data element at the root node of a Min-Heap must be the smallest (or least) of all the data elements in the tree.

    (Source:   logicmojo

     
  20. What is LIFO?
    The acronym LIFO stands for Last In First Out. It is the act of retrieving, storing, and accessing data. Using this scheme, the data that was stored last should be extracted first. This also indicates that all preceding data must be retrieved and extracted before the initial data can be accessed.

     
  21. What are multidimensional arrays?
    An array with more than one dimension is called a multidimensional array. It's either an array of arrays or a multi-layer array. The most basic multidimensional array is the two-dimensional array or 2D array. As you'll see in the code, it's technically an array of arrays. A matrix or a table with rows and columns is another name for a two-dimensional array. A multidimensional array and a one-dimensional array are the same things. We must tell C that we have two dimensions for a two-dimensional array.
     
  22. What is dynamic memory allocation, and how does it help in managing data?
    The process of assigning memory space during execution or run time is known as dynamic memory allocation. 

    → Dynamic memory allocation can join individually allocated structured blocks to construct composite structures that expand and shrink as needed, in addition to storing simple structured data types.
    → Dynamic memory allocation allows you to assign memory to a process in a variety of ways.
    → Assigning memory to a process during the execution of that programme, dynamic memory allocation decreases memory waste.
     
  23.  What is FIFO?
    First-in, first-out (FIFO) is a term that describes how data is accessed in a queue. The data that has been added to the queue list the longest gets eliminated first.

     
  24. Differentiate NULL and VOID
    Void is a data type identifier, whereas Null is a value. A variable with the value Null represents an empty variable. The void is used to indicate pointers that do not have an initial size.
     
  25. What is a Red-Black Tree?
    A binary tree with nodes represented by two colours: red and black, is known as a red-black tree. The tree follows specific attributes.

    These include:
    → The tree's root node is always black.
    → The number of black nodes on each path from the root to any of the leaf nodes should be the same.
    → There can't be any red nodes next to each other.

     
  26. How to implement a queue using a stack? 
    There are two approaches for implementing a queue utilising two stacks. One by increasing the cost of enqueueing and the other by increasing the cost of dequeuing.
    For a detailed understanding, follow this blog.
     

Check out this problem - Reverse Nodes In K Group

Read about Application of Queue in Data Structure here.

FAQs

What is data abstraction?

Data abstraction helps in dividing complex data problems into smaller, easy-to-manage parts. It begins by defining all of the related data items as well as the numerous operations to be done, without regard for how data is stored.

Why are linear data structures easy to implement?

Because computer memory is organised in a linear fashion, linear data structures are simple to build. Array, stack, queue, linked list, and others are examples.

What is the complexity of adding an element to the heap.

O(N), Explanation: The total number of operations allowed in relocating the new location to a new element is equal to the heap's height.

What happens to the data inserted first in a queue?

Data inserted initially will be the first to leave the queue. Enqueue is the process of adding an element to a queue, while Dequeue is the process of removing an element from a queue. A queue, like a stack, is an ordered list of elements of comparable data types. The structure of a queue is FIFO (First in, First Out).

How many stacks are needed to implement a queue?

We need two stacks to implement a queue..
 

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Conclusion

In this article, we have extensively discussed Data Structure Interview Questions.

  • We have learned about data structures, types and their applications in the real world. 
  • We have learned important data structure interview questions.

We hope that this blog has helped you enhance your knowledge regarding Data Structure Interview Questions, and if you would like to learn more, check out our articles on Linux interview questions part1Linux interview questions part2AWS interview questions, and Selenium interview questions, Pandas Interview Questions for further interest visit these links on data structures and algorithmscontestsinterview experiencesguided pathslibrarytest seriesproblemsstack and queues interview questionscrack technical interview. Do upvote our blog to help other ninjas grow.

 

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