Our Support: During the COVID-19 outbreak, we request learners to CALL US for Special Discounts!

- Data Analyst Blogs -

Important Interview Questions on Data Structures

Have a big interview for data science and java based job roles? Worried about what data structures interview questions Java-Based to prepare? There is nothing to panic about, if you have a list of interview questions on data structures & algorithms or on data structures interview questions in JAVA around you, you will be good to go. Here is the complete list of important algorithms and data structures interview questions JAVA-based that you must overlook and prepare with great confidence.

Important Interview Questions on Data Structures 1

Most Asked Interview Questions on Data Structures and Algorithms 

1. What is Data Structure?

Data Structure is data collection, management, and storage format for easy access & modification. In other words, it is a collection of data values and the relationship between them and functions & operations that can be applied to these values. 

2. What are the types of data structures? 

Data Structures are mainly of the following two types: 

  1. Linear Data structure - A data structure is linear when its elements are in sequential order or are a linear list and every element is placed in a non-hierarchical manner.

           Few examples - Arrays, Stack, Strings, Queue, and Linked List. 

  1. Non-Linear Data structure - When the elements of the data structure are not arranged in a sequential manner and instead the element is attached with two or more elements in a non-linear arrangement.

           Few examples - Graphs & trees. 

3. In what most areas the data structures are used? 

Data structures are part of the following branch of computer science: 

  1. AI
  2. DMS - Database management systems
  3. Numerical Analysis
  4. Simulation
  5. Statistical analysis package
  6. Compiler design
  7. Operating system
  8. Compiler design 

4. The linked list is an example of a linear or non-linear data structure? 

A linked list can be a subset of both linear and nonlinear, it depends on its usage & application. If it is used for access strategies, then it is a part of linear structures but when used for data storage, it can be called a non-linear data structure. 

3. What is the linked list data structure? 

It is simply a sequence of data objects where elements of data structures are not stored in adjacent memory locations. Each element is inside such a setting is an individual object called a node. Every node has 2 items, one is a data field and the other is a reference to the next node. Head is the entry point in each linked list. When the list is empty, the head is a null reference and the last node has a reference to null. 

Data Science Training - Using R and Python

  • Detailed Coverage
  • Best-in-class Content
  • Prepared by Industry leaders
  • Latest Technology Covered

6. What is the algorithm? 

The algorithm is a defined procedure, which demonstrates the actions or steps to be executed in a certain order to get the desired outputs. 

7. What different operations can be performed on any data structure? 

  • Sorting - To arrange the data in ascending or descending order, when there is numerical data or in dictionary order when the data is in alphanumeric form.
  • Searching - To search the location of the data item if it is available in the given data items collection.
  • Deleting - To delete no longer required data from the given data items collection.
  • Insertion - To add new data in the given collection of data items.
  • Transversal - To access each data item exactly as it is to help with further processing. 

8. What is the difference between an Array and Linked list? 

  • Linked lists are dynamic size, whereas arrays have a fixed size.
  • The linked list allows easy insertion & deletion of data, whereas performing insertion & deletion in arrays is quite expensive.
  • You cannot have random access to the linked list.
  • Arrays have great cache locality which adds to the great performance.
  • In each element of the linked list, extra memory space is needed for the pointer. 

9. What is a doubly-linked list? Mention some examples to it. 

A doubly linked list is a complex type of linked list, further in which each node has two links, the first link connects to the next node pinned in the sequence, whereas the second link is connected to the previous node. It allows for easy transversal between the data elements in different directions. 

Here are the few examples of doubly linked list: 

  1. The music or video playlist with next & previous buttons for navigation.
  2. The browser cache having back-forward visited pages.
  3. The undo & redo functions over a web browser that helps to get to the previous page. 

11. What are dynamic data structures? Mention a few. 

Read: How to Become a Successful Data Analyst?

Dynamic data structures are a collection of data in memory that expands and shrinks as per the program. And allows the programmer to regulate memory utilization as per requirement. 

The few examples of dynamic data structures are slack, queue, heap, linked list, and array.  

12. Why is algorithm analysis required? 

A problem can be solved in too many ways. To treat computational problems, the algorithm analysis provides an estimation of the required resources and also helps to determine the time and space these resources would require to execute. 

13. What is stack and for what it is used? 

A stack is a data type that defines a linear data structure with an order - LIFO (Last in first out) or FILO (first in last out). Three basic operations /functions of the stack are - Pop, peek and push. 

Stacks are used for:- 

  • Backtracking
  • Parenthesis check
  • Syntax parsing
  • String reversal
  • Evaluation & conversion of evaluating prefix, postfix, and infix expressions 

14. What are the queue data structures? List some of its applications. 

The queue data structure is a data type that specifies the ordered list or linear data structure by using the first in first out (FIFO) operation for gaining access to elements. In such a structure, insert operations are done at the end “REAR” and delete operations are done on the other end called “FRONT”. 

Here are some of the applications of queue data structures:

  • While maintaining (adding or deleting) the songs in the playlist.
  • During the asynchronous transfer of data - file, sockets or so.
  • As buffers in CD players in MP3 media players.
  • As for waiting lists in call center systems, CPUs, printers. 

Data Science Training - Using R and Python

  • No cost for a Demo Class
  • Industry Expert as your Trainer
  • Available as per your schedule
  • Customer Support Available

15. What do you mean by Dequeueue? 

Dequeue is a data structure that is a double-ended queue, in which data can be deleted and inserted from both ends which are - REAR and FRONT. 

16. Where usually stack data structure is used? 

Stack structure has its application in - 

  • Memory management
  • Function calling and return
  • Expression evaluation
  • Backtracking 

17. Why is Heap more advantageous than Stack? 

Heap and Stack both of them are part of memory and are often required for use in JAVA for multiple needs: But here what makes them incomparable: 

  • Heap is quite flexible compared to stack because it can easily allocate and deallocate the memory space.
  • Stacks contained variables seem visible only to the private owners, while objects gathered in Heap are visible to all threads.
  • Stack memory just holds local variables & function calls while heap memory is used to store objects in JAVA.
  • While recursion, the stack memory fills-ups quickly, while Heap memory doesn’t. 

18. What is the difference between PUSH & POP? 

PUSH and POP help to define how the data should be stored and retrieved within a stack. 

  • PUSH explains that data has been put or inserted into the stack.
  • While POP defines that the data has been retrieved or deleted from the stack. 

19. What do you mean by Postfix expression? 

Postfix expression is an expression where the operators follow the operands. The best part of this expression is: 

  • No grouping of sub-expressions required in parenthesis
  • No need to consider operator precedence

For example - If you write -  a+b, it will be shown as ab+ in postfix. 

20. Which sorting algorithm is the fastest and why? 

QuickSort Algorithm has considered the fastest it delivers the best performance with more inputs. Here are the reasons why this algorithm is said to be best & fastest over other sorting algorithms: 

  • Even if it has a worse-case input set, it will still be efficient as the order is random.
  • It is cache efficient as it linearly scans and partitions the input.
  • Being slightly sensitive to input, it skips swaps.
  • Can easily adapt complete or mostly sorted inputs.

 

21. What do you mean by merge sort and how does it work? 

Read: 23 Best Data Analysis Tools For 2020 & Beyond

Merge sort is a type of a divide and conquer algorithm that helps in sorting the data. This merges & sorts the adjacent data and develops bigger sorted lists out of it, these multiple lists are merged recursively to form even bigger sorted lists - until you don’t get a final and single sorted list. 

22. Explain the graph data structure. 

It is a kind of non-linear data structure that contains vertices or nodes connected by arcs to allow storing and retrieval of data. Arcs or edges can be directed or undirected. 

23. What are some of the applications of the Graph data structure? 

Graph data structures are used for: 

  • Social network graphs - To understand the flow of information and hotspots.
  • Utility graphs for power or water - in which vertices are connection points & edge the wires connecting them.
  • Neural networks
  • Transport grids  

24. Why is binary search advantageous over linear search? 

  • The binary search runs in 0 (log n) time while the linear search runs on the 0 (n) time. This means if there are more elements in the search array, the binary search would be faster than the linear search.
  • Another reason why binary is faster because, in its way, it performs fewer comparisons. During the linear search, only a single element can be eliminated during the per element comparison, while during the binary search, it is possible to eliminate half of the set during each element comparison. 

25. What is the difference between NULL and Void? 

  • The void is a data type identifier while NULL is a value.
  • Void indicates that the pointer has no initial size while NULL indicates an empty value for a variable.
  • Void means that value exists but is not in effect while Void means that the value never existed. 

26. What are the 2 ways to determine whether the linked list has a loop? 

  • By Floyd’s cycle-finding algorithm
  • By using the visited nodes method
  • By using Hashing 

27. Where multilinked structures are commonly used? 

Multi linked structures are most used to generate an index and sparse matrix. 

28. What is the structure of the max heap data structure? 

In max heap data structures, the value of the root node stands as either equal or greater to its child nodes. 

29. What is Jagged array? 

An array where its elements are itself arrays of different sizes & dimensions. 

30. How does dynamic memory allocation help with the management of data? 

Dynamic memory allocations carry the simple data structure types during the runtime. It helps to combine the separately allocated blocks to turn them into a composite structure - that could be extended and shrunken as needed. Thus, it helps with data blocks of arbitrary size and arbitrary order. 

31. List out of the types of trees. 

There is a total of 6 types of trees: 

  • Tournament tree
  • Expression tree
  • Binary tree
  • Binary search tree
  • General tree
  • Forests 

32. What is bubble sort and how does it work? 

Bubble sort is a comparison based algorithm, where every pair of adjacent elements is compared, and these elements are swapped if they are not placed in order.  

33. How file structure & storage structure are different? 

Storage structures define the data structure in the memory of the computer system while file structure defines the storage structure in the auxiliary memory. 

34. What are some of the applications of the Tree-data structure? 

The tree data structure has the following applications: 

  • Syntax analysis
  • Symbol table construction
  • Hierarchical data model
  • Manipulation of an arithmetic expression 

35. State the difference between path, cycle, circuit. 

  • Circuit -  it is a closed path where initial vertex and end vertex are identical to each other. And any vertex can be repeated.
  • Path - They are the sequence of adjacent vertices that are connected by edges and have no restrictions.
  • Cycle - It is also a closed path where the initial vertex is identical to the closed vertex but the vertex in the path cannot be visited twice. 

36. What is a spanning tree and how many do such trees a graph have? 

Spanning tree is a subset of Graph G that has all the vertices covered with the least number of edges. Such trees do not have a cycle, they cannot be disconnected. 

Read: Top 30 Data Analyst Interview Questions And Answer

The number of such trees depends on how the graph is connected. Say a complete undirected graph can have n(n-1) number of spanning trees - where n calls for nodes. 

Data Science Training - Using R and Python

  • Personalized Free Consultation
  • Access to Our Learning Management System
  • Access to Our Course Curriculum
  • Be a Part of Our Free Demo Class

37. Which data structures must be used to perform LRU cache? 

You can use two data structures to perform LRU cache: 

  • Hash- With page number as key and address of the corresponding queue node as the value.
  • Queue - This structure is performed using a doubly-linked list. The recently used pages will be found near the REAR end and the least recently used pages near the front end. 

38. What are the benefits of Selection sort?

 The selection sorts are: 

  • Quite simple and easy to perform.
  • Are 60% more effective than the bubble sort?
  • Are suitable for small data sets. 

39. What are the limitations of the array implementation of Queue? 

The size of the array - If we need to add more elements in the queue, we need to expand the size of the queue, but by chance, if we are using an array to implement a queue, it is not possible to extend the array size, therefore, array implementation of the queue is often a problem. 

Waste of memory- The space of the array that is used for storing queue elements cannot be reused to store the queue elements because the elements can only be put in from the front end,  and the value of the front end is so high that all the space before that will not be filled completely. 

Hope you have got the interview questions on data structures and algorithms or data structures interview questions JAVA-based. We have a complete bank of data structures interview questions, for which you can consult us. We will lead you to helpful ways to strengthen your practice for algorithms and data structures interview questions. 

Conclusion

If you have been looking for data structures interview questions in java, these are a few important algorithms and data structures interview questions. To understand the components of data structures in-depth, a learning guide is most required.  

If you wish to crack your data science and java based job interviews, knowing and preparing these interview questions on data structures and algorithms can easily help. 

But to know more of algorithms and data structures interview questions or data structures interview questions in java, you can buy our Data science self-learning kit, where you will find complete packaged knowledge on data structures and others - from concepts to interviews questions, you will be served with comprehensive knowledge. While if you are confused at how to prepare interview questions on data structures Java-based, you can even reach out to our instructors who will help you find the finest & effective ways to prepare and crack these questions during the interview processes. 

 

 

 

 

 

 

 

 

 




    Janbask Training

    A dynamic, highly professional, and a global online training course provider committed to propelling the next generation of technology learners with a whole new way of training experience.


Comments

Trending Courses

AWS

  • AWS & Fundamentals of Linux
  • Amazon Simple Storage Service
  • Elastic Compute Cloud
  • Databases Overview & Amazon Route 53

Upcoming Class

-1 day 14 Jul 2020

DevOps

  • Intro to DevOps
  • GIT and Maven
  • Jenkins & Ansible
  • Docker and Cloud Computing

Upcoming Class

16 days 31 Jul 2020

Data Science

  • Data Science Introduction
  • Hadoop and Spark Overview
  • Python & Intro to R Programming
  • Machine Learning

Upcoming Class

1 day 16 Jul 2020

Hadoop

  • Architecture, HDFS & MapReduce
  • Unix Shell & Apache Pig Installation
  • HIVE Installation & User-Defined Functions
  • SQOOP & Hbase Installation

Upcoming Class

2 days 17 Jul 2020

Salesforce

  • Salesforce Configuration Introduction
  • Security & Automation Process
  • Sales & Service Cloud
  • Apex Programming, SOQL & SOSL

Upcoming Class

0 day 15 Jul 2020

QA

  • Introduction and Software Testing
  • Software Test Life Cycle
  • Automation Testing and API Testing
  • Selenium framework development using Testing

Upcoming Class

9 days 24 Jul 2020

Business Analyst

  • BA & Stakeholders Overview
  • BPMN, Requirement Elicitation
  • BA Tools & Design Documents
  • Enterprise Analysis, Agile & Scrum

Upcoming Class

-1 day 14 Jul 2020

MS SQL Server

  • Introduction & Database Query
  • Programming, Indexes & System Functions
  • SSIS Package Development Procedures
  • SSRS Report Design

Upcoming Class

0 day 15 Jul 2020

Python

  • Features of Python
  • Python Editors and IDEs
  • Data types and Variables
  • Python File Operation

Upcoming Class

8 days 23 Jul 2020

Artificial Intelligence

  • Components of AI
  • Categories of Machine Learning
  • Recurrent Neural Networks
  • Recurrent Neural Networks

Upcoming Class

-1 day 14 Jul 2020

Machine Learning

  • Introduction to Machine Learning & Python
  • Machine Learning: Supervised Learning
  • Machine Learning: Unsupervised Learning

Upcoming Class

2 days 17 Jul 2020

Tableau

  • Introduction to Tableau Desktop
  • Data Transformation Methods
  • Configuring tableau server
  • Integration with R & Hadoop

Upcoming Class

8 days 23 Jul 2020

Search Posts

Reset

Receive Latest Materials and Offers on Data Analyst Course

Interviews