problem solving in data structures and algorithms using c#

Crack the top 45 C# data structure questions

Complexity Measures Questions

C# linked lists, c# stacks and queues, c# trees and tries, c# heaps and hashing.

• 20 more questions for C# coding interview

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Ace your c# interview the first time practice hundreds of common interview questions with hands-on code environments and instant feedback. data structures for coding interviews in c#, 1. big o complexity: nested addition.

Find the Big O complexity of the following code snippet.

2. Big O complexity: Nested Multiplication

3. big o with nested multiplication (advanced).

Find the Big O complexity of the following code snippet:

4. Remove even integers from an array

Implement a function removeEven( int[]Arr, int size ) , which takes an array arr and its size and removes all the even elements from the given array.

For example:

Solution and Explanation

Time Complexity : O ( n ) O(n) O ( n )

This solution first checks if the first element of Arr is odd. Then it appends this element to the start of the array Arr ; otherwise, it jumps to the next element. This repeats until the end of the array Arr is reached while keeping the count of total odd numbers m in Arr . Next, we make a temporary array, temp , to store all odd numbers.

From there, we delete the memory allocated to Arr , and point it to the temp array. Lastly, we return the array Arr that is, which now contains only odd elements.

5. Find the minimum value in an array

Implement a function findMinimum(int arr[], int size) , which takes an array arr and its size and returns the smallest number in the given array.

Start with the first element (which is 9 in this example), and save it as the smallest value. Then, iterate over the rest of the array. Whenever an element that is smaller than minimum is found, set minimum to that number.

By the end of the array, the number stored in minimum will be the smallest integer in the whole array.

6. Maximum subarray sum

Given an unsorted array Arr , find the collection of contiguous elements that sums to the greatest value.

Hint : Remember that the array could contain negative numbers.

This solution uses Kadane’s algorithm to scan the entire array.

Take a look at Kadane’s algorithm in pseudocode:

At each position in the array, we find the maximum sum of the subarray ending there. This is achieved by keeping a currMax for the current array index and a globalMax . By the end, we know that the value of globalMax will be the highest subarray, regardless of the value of currMax .

Below are the Node and LinkedList classes available for you to use throughout this section:

7. Insertion at Tail

Create a function insertAtTail() that takes an integer, adds the integer to the end of a linked list, and returns the updated linked list. The new node will point to null .

If the list is empty, the situation is exactly like insertion at the head.

Otherwise, you can simply use a loop to reach the tail of the list, and set your new node as the nextElement of the last node.

8. Remove Duplicates from a Linked List

Implement the removeDuplicates() function, which takes a linked list and returns the linked list with no duplicate nodes.

Time Complexity : O ( n 2 ) O(n^2) O ( n ​ 2 ​ ​ )

In this implementation, we check each node against the remaining list to see if a node contains an identical value.

start iterates through the outer loop, while startNext checks for duplicates on line 90 in LinkedList.cs .

Whenever a duplicate is found, it is removed from the list using line 103 .

9. Join two linked lists

Implement the Union() function that takes two linked lists and returns a single linked list that contains all unique elements from both linked lists.

Time Complexity : O ( m + n ) 2 O(m + n)^2 O ( m + n ) 2 where m is the size of the first list, and n is the size of the second list.

Traverse to the tail of the first list, and link it to the first node of the second list on line 125 - 131 in LinkedList.cs . Now, remove duplicates from the combined list.

Below are the implementations of Stacks and Queues available for you to use throughout this section:

10. Generate binary numbers from 1 to N

Implement a function string [] findBin(int n) , which generates binary numbers from 1 to n stored in a String array using a queue.

On line 17 , 1 is enqueued as a starting point. Then, a number is dequeued from the queue and stored in the result array to generate a binary number sequence.

On lines 22-23 , 0 and 1 are appended to it to produce the next numbers, which are then also enqueued to the queue on lines 24-25 . The queue takes integer values. Before enqueueing, the solution makes sure to convert the string to an integer.

The size of the queue should be one more than n because you are enqueuing two variations of each number; one is appended with 0 , and one with 1 .

11. Implement a queue using stacks

Use the myStack class to implement the enqueue() function in the NewQueue class. enqueue() takes an integer and returns true after inserting the value into the queue.

This approach, uses two stacks. The mainStack stores the queue elements and the tempStack acts as a temporary buffer to provide queue functionality.

Make sure that after every enqueue operation, the newly inserted value is at the bottom of the main stack.

Before insertion, all the other elements are transferred to tempStack and naturally, their order is reversed. The new element is added into the empty mainStack . Finally, all the elements are pushed back into mainStack and tempStack becomes empty.

12. Find the lowest value in a stack

Implement the minStack class with the function min() , which returns the lowest value in the stack. min() must have a complexity of O ( 1 ) O(1) O ( 1 ) .

Hint : The element is returned , not popped.

Time Complexity : O ( 1 ) O(1) O ( 1 )

The whole implementation relies on the existence of two stacks: minStack and mainStack .

mainStack holds the actual stack with all the elements, whereas minStack is a stack whose top always contains the current minimum value in the stack.

Whenever push is called, mainStack simply inserts the new value at the top.

However, minStack checks the value being pushed. If minStack is empty, this value is pushed into it and becomes the current minimum. If minStack already has elements in it, the value is compared with the top element.

If the value is lower than the top of minStack , it is pushed in and becomes the new minimum. Otherwise, the top remains the same.

Due to all these safeguards put in place, the min function only needs to return the value at the top of minStack .

Below is an implementation of a Graph available for your use throughout this section. The Graph Class consists of two data members:

• The total number of vertices in the graph
• A list of linked lists to store adjacent vertices

13. Implement Depth First Search (DFS)

Implement a Depth First Search algorithm that can find a passed integer within a graph.

Depth First Search : Starts at the graph’s root node and explores as far as possible along each branch before backtracking.

Time Complexity : O ( V + N ) O(V + N) O ( V + N )

The approach is very similar to that of the BFS solution. However, instead of a queue, use a stack since it follows the Last In First Out (LIFO) approach. You will see how that is useful in this situation.

dfsTraversal calls the helper function dfs_helper on every vertex, which is not visited. dfs_helper starts from source and each node is pushed into the stack. Whenever a node is popped, it is marked “visited” in the visited array, and its adjacent nodes are pushed into the stack.

The stack is helpful because it pops out the new adjacent nodes instead of returning the previous nodes that you pushed in.

14. Find a “Mother Vertex” in a graph

Implement the int findMotherVertex(Graph g) function, which will take a graph as input and find out a mother vertex in the graph. By definition, the mother vertex is one from which all other vertices are reachable.

Time Complexity : O ( V + E ) O(V + E) O ( V + E )

This solution is based in Kosaraju’s Strongly Connected Component Algorithm.

Initially, we run the Depth First Search on the whole graph in a loop on line 17 . The DFS ensures that all the nodes in the graph are visited. If the graph is disconnected, the visited array will still have some vertices, which haven’t been set to true.

The theory is that the last vertex visited in the recursive DFS will be the mother vertex because at the last vertex, all slots in visited would be true (DFS only stops when all nodes are visited); hence, keeping track of this last vertex using lastV .

Then reset the visited array, and run the DFS only on lastV . If it visits all nodes, it is a mother vertex. If not, a mother vertex does not exist.

The only limitation in this algorithm is that it can only detect one mother vertex even if others exist.

15. Remove edge

Implement the remove_Edge() function that takes a source and destination node and deletes any edge between the two.

Reminder : An edge is the connection between two nodes in a graph.

Time Complexity : O ( E ) O(E) O ( E )

Edge connections are handled by our source linked list. We’ll access this source linked list and call our delete() function from line 127 on the node connections between 2 and 3 .

delete() essentially searches for a passed value then removes the node by redirecting the pointer.

Keep practicing C#.

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Data Structures for Coding Interviews in C#

Below is an implementation of Binary Search Trees available for your use in this section.

16. Find the lowest value in a Binary Search Tree

Implement int findMin(Node* rootNode) , which takes a Binary Search Tree and returns the lowest value within the tree.

Remember : Nodes in the left subtree of a current node will always be lower, while the right subtree will always be greater.

Time Complexity : O ( h ) O(h) O ( h )

This solution is recursive to increase efficiency. The sorted structure of a BST makes this solution easier because we just have to find the left-most node.

First, we check if the root is null . If it is, we return -1 ( lines 10-11 ). Otherwise, we check to see if the left child of the current node is null . If it is, then this root is the leftmost node, and you return the value there ( lines 12-13 ).

If a left node exists, call the findMin() function on it ( lines 14-15 ).

17. Find the height of a BST

Implement int findHeight(Node* rootNode) , which takes a binary search tree and returns its height.

The height of a tree is equal to the number of edges between the root node and the lowest node.

The height of your tree equals the greatest height from either the left or right subtree.

Therefore, we must recursively find the heights of the left and right-subtrees. First, we check if the tree is empty, returning -1 if the given node is null . If not, we call the findHeight() function on the left and right-subtrees and return the one that has a greater value plus 1.

18. 2-3 Trees vs. BST

What is the difference between 2-3 Trees and Binary Search Trees?

19. Insertion in a Trie

Implement the insertNode(string key) function, which takes a word and inserts it into an existing trie.

Remember : Consider the three cases for insertion: no common prefix, common prefix, and existing word.

The function takes a string key , indicating a word. NULL keys are not allowed, and all keys are stored in lowercase.

First, we iterate over the characters in the key. For each character, we generate an index using getIndex() .

The next step is to check the child of currentNode at that particular index. If it is NULL , then we create a new TrieNode at that index.

In the end, we mark the last node as a leaf since the word has ended.

20. Total words in a Trie

Implement the totalWords() function, which will take a trie and return the total number of words in the trie.

Starting from the root, we visit each branch recursively. Whenever a node is found with isEndWord set to true, the result variable is incremented by 1.

At the end, we return result to state the total number of words.

21. Implement a Max-Heap

A max-heap is a complete binary tree in which the value of each internal node is greater than or equal to the values in the children of that node.

Your max-heap must include insert() and delete() functions but can also contain any additional functionalities.

Notice that you start from the bottom of the heap, i.e., i = size-1 ( line 78 ). If the height of the heap is h , then the levels go from “0” (at the root node) to “h” at the deepest leaf nodes. By calling maxHeapify() at the leaf nodes, you will have a constant time operation.

At level h - 1h−1 , for every node, maxHeapify() makes one comparison and swap operation at most. At level h−2 , , it makes two at most comparisons and swaps for every node. This continues until the root node, where it makes h comparisons at most, swaps operations.

22. Find k smallest elements in an array

Implement a function findKSmallest(int[] arr, int size, int k) that takes an unsorted integer array as input and returns the “k” smallest elements in the array by using a heap.

You can use the following minHeap implementation as a starting point:

Time Complexity : O ( n + k l o g n ) O(n + klogn) O ( n + k l o g n )

Here create a heap and then call the buildHeap ( line 12 ) function to create a minimum heap from the given array. To find the k smallest elements in an array:

You get the minimum value from the heap.

Save the result to the vector output.

Remove the minimum value from the heap.

Repeat the same steps k times (provided k < size ).

23. Trie vs. Hash Table

Compare the use and performance of Tries and Hash Tables.

24. Subset Array Checker

Implement the isSubset(int[] arr1, int[] arr2, int size1, int size2) function, which will take two arrays and their sizes as input and check if one array is the subset of the other.

The arrays will not contain duplicate values.

Time Complexity : O ( m + n ) O(m+n) O ( m + n ) where m is the number of elements in arr1 and n is the number of elements in arr2 .

C# built-in HashSet makes this solution much simpler. First, we iterate over arr1 on line 16 . If the value at the current index is not present in the HashSet , we insert that value in the HashSet on lines 20-21 . Then, we iterate through arr2 to see whether their elements are present in HashSet .

If all the elements of arr2 are present in HashSet , then your function will return true lines 25-32 .

25. Find two pairs with an equal sum

Implement the string findPair(int[] arr, int size) function, which will take an array and find two pairs, [a, b] and [c, d] , in an array such that:

a + b = c + d a+b = c+d a + b = c + d

Remember : You only have to find any two pairs in the array, not all pairs.

Time Complexity : O ( n 2 ) O(n^2) O ( n 2 )

This solution uses C#'s built-in Dictionary class for simplicity.

On lines 23-33 , each element in arr is summed with all other elements. The sum becomes the key in the hMap . At every key, store the integer pair whose sum generated that key.

Whenever a sum is found such that its key in the hMap already has an integer pair stored in it, you can conclude that this sum can be made by two different pairs in the array. These two pairs are then returned in the result array on lines 36-46 .

20 more questions for a C# coding interview

• Reverse a string in C#
• Check if a given string is a palindrome
• Rotate an array
• Find the second largest integer within an array using one loop
• Convert a 2D Array to a 1D Array
• Explain and implement the MergeSort algorithm
• Find out if a linked list is circular
• Balance a binary search tree
• Search a sorted array with lowest time complexity possible
• 0-1 Knapsack problem
• Reverse a linked list
• Match beginning and ending parenthesis in a string
• Shuffle an array of integers in place
• Find the ancestors of a given node in a BST
• Find the shortest path between two vertices in a graph
• Count the number of edges in an undirected graph
• Check balanced parenthesis using a stack
• Sort values in a stack
• Reverse first k elements in a queue
• Find the middle node of a linked list

Great work on those questions! The best way to prepare for your next interview is to keep getting hands-on practice with common data structure questions like these.

To help your prepare for your interview right, Educative has created the course Data Structures for Coding Interviews in C# . This course lets you hone your data structure skills with hundreds of practice questions, each with live coding environments and in-depth explanations.

By the end of the course, you’ll be an expert on identifying and solving all the most-asked interview question patterns.

Happy learning!

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Book description

Write sophisticated C# code with this complete guide to using diverse data structures and algorithms, featuring ready-to-use code snippets, detailed explanations, and illustrations

Key Features

• Master lists, stacks, queues, dictionaries, sets, and trees, among other data structures
• Delve into effective design and implementation techniques to meet your software requirements
• Visualize data structures and algorithms through illustrations for a clearer understanding of their analysis
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Building your own applications is exciting but challenging, especially when tackling complex problems tied to advanced data structures and algorithms. This endeavor demands profound knowledge of the programming language as well as data structures and algorithms – precisely what this book offers to C# developers.

Starting with an introduction to algorithms, this book gradually immerses you in the world of arrays, lists, stacks, queues, dictionaries, and sets. Real-world examples, enriched with code snippets and illustrations, provide a practical understanding of these concepts. You’ll also learn how to sort arrays using various algorithms, setting a solid foundation for your programming expertise. As you progress through the book, you’ll venture into more complex data structures – trees and graphs – and discover algorithms for tasks such as determining the shortest path in a graph before advancing to see various algorithms in action, such as solving Sudoku.

By the end of the book, you’ll have learned how to use the C# language to build algorithmic components that are not only easy to understand and debug but also seamlessly applicable in various applications, spanning web and mobile platforms.

What you will learn

• Understand the fundamentals of algorithms and their classification
• Store data using arrays and lists, and explore various ways to sort arrays
• Build enhanced applications with stacks, queues, hashtables, dictionaries, and sets
• Create efficient applications with tree-related algorithms, such as for searching in a binary search tree
• Boost solution efficiency with graphs, including finding the shortest path in the graph
• Implement algorithms solving Tower of Hanoi and Sudoku games, generating fractals, and even guessing the title of this book
• Who this book is for

This book is for developers looking to learn data structures and algorithms in C#. While basic programming skills and C# knowledge is useful, beginners will find value in the provided code snippets, illustrations, and detailed explanations, enhancing their programming skills. Advanced developers can use this book as a valuable resource for reusable code snippets, instead of writing algorithms from scratch each time.

Table of contents

C# data structures and algorithms.

• Contributors
• About the author
• About the reviewer
• What this book covers
• To get the most out of this book
• Download the example code files
• Conventions used
• Get in touch
• Share Your Thoughts
• Download a free PDF copy of this book
• C# as a programming language
• .NET-based console applications
• Division of data types
• Integral numbers
• Floating-point numbers
• Boolean values
• Unicode characters
• Enumerations
• Value tuples
• User-defined structs
• Nullable value types
• Nullable reference types
• Real-world examples
• Natural language
• Programming language
• Recursive algorithms
• Divide and conquer algorithms
• Back-tracking algorithms
• Greedy algorithms
• Heuristic algorithms
• Dynamic programming
• Brute-force algorithms
• Time complexity
• Space complexity
• Example – month names
• Example – multiplication table
• Example – game map
• Example – yearly transport plan
• Selection sort
• Insertion sort
• Bubble sort
• Performance analysis
• Array lists
• Generic lists
• Example – address book
• Singly linked lists
• Doubly linked lists
• Circular singly linked lists
• Circular doubly linked lists
• List-related interfaces
• Example – reversing a word
• Example – Tower of Hanoi
• Example – call center with a single consultant
• Example – call center with many consultants
• Example – call center with priority support
• Example – gravity roller coaster
• Example – phone book
• Example – product location
• Example – user details
• Example – encyclopedia
• Example – coupons
• Example – swimming pools
• Example – removing duplicates
• Implementation
• Example – hierarchy of identifiers
• Example – company structure
• Example – simple quiz
• Example – BST visualization
• Red-black trees
• Example – autocomplete
• The concept of graphs
• Applications
• Adjacency list
• Adjacency matrix
• Example – undirected and unweighted edges
• Example – directed and weighted edges
• Depth-first search
• Breadth-first search
• Kruskal’s algorithm
• Prim’s algorithm
• Example – telecommunication cable
• Example – voivodeship map
• Example – path in game
• The Fibonacci series
• Minimum coin change
• Closest pair of points
• Fractal generation
• Rat in a maze
• A Sudoku puzzle
• Title guess
• A password guess
• Classification
• Dictionaries
• The last word
• Why subscribe?
• Packt is searching for authors like you

Product information

• Title: C# Data Structures and Algorithms - Second Edition
• Author(s): Marcin Jamro
• Release date: February 2024
• Publisher(s): Packt Publishing
• ISBN: 9781803248271

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Most Recommended Data Structure and Algorithms Books using C#

Back to: C#.NET Tutorials For Beginners and Professionals

In this article, I will provide the list of the Most Recommended Data Structure and Algorithms Books using C# for Students, Beginners, and Professional Software Developers. If you want to start your carrier as a developer then understanding Data Structure and Algorithms is a must. Books are the best friend of students as well as developers and the first mode of learning new Languages, Frameworks, and Technologies and nothing can beat books when it comes to educating. It is the reason most experienced C# Developers recommend reading books for learning Data Structure and Algorithms. 

Combining the best C# Data Structure and Algorithms books along with articles, tutorials, and videos, you will get an excellent path to learning Data Structure and Algorithms using C# Language. Some of the books just give an overview of various Data Structure and Algorithms concepts, while some other Data Structure and Algorithms books go into the depth of each Data Structure and Algorithms concept.

There are hundreds and thousands of Data Structure and Algorithms books using C# available on Amazon or Internet or any other e-commerce site. And as a beginner, you might be confused to choose the right book to start learning Data Structure and Algorithms. Here, we are giving you a list of Data Structure and Algorithms Books using C# Language based on the experience of Learners and Professionals Developers. If you still haven’t put together your reading list, we’re here to help with our choice of the best-recommended books for Data Structure and Algorithms using C#.

1. Easy Learning Data Structures & Algorithms C#

Data Structures and Algorithms C# Practice, It is designed to be easy to read and understand although the topic itself is complicated. Algorithms are the procedures that software programs use to manipulate data structures. Besides clear and simple example programs. The programs demonstrate in graphical form what data structures look like and how they operate.

The complexity of life, because they do not understand to simplify the complex, simple is the beginning of wisdom. From the essence of the practice, this book briefly explains the concept and vividly cultivates programming interest, you will learn it easily, fast, and well.

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2. Arrays and Time Complexity Implementation Solutions in C#

This e-book is all about Arrays and how to use arrays in various time complexity scenarios situations, to solve real-life problems. It illustrates the common, and essential data structures algorithms, underscoring array processing with time complexity. It also details, with examples, how to go about creating step by step algorithm solutions, for solving array data-structure problems, such as Finding in basic and complex arrays, Pythagorean triplets (Using a 4-Algorithm Approach: Simple, Sorting, Hashing-Like, and HashSet algorithms, and when to use them), Finding the 2nd Largest Number in basic and complex arrays (Using a 3-Algorithm Approach: Simplest, Better than Simplest, and Most-Efficient algorithms), Finding in basic and complex arrays, local minima (defined as a number in an array, that is less than both of its neighbours, on its left and right), local maxima (defined as a number in an array, that is greater than both of its neighbours, on its left and right), and local extrema (defined as any number in an array, that is a local minima or a local maxima), Getting array positions based on its elements in basic and complex arrays, Finding in basic and complex arrays, missing element/s, How to remove duplicate elements in basic and complex arrays, How to find in basic and complex arrays, the missing and repeated elements, How to find in basic and complex arrays, two missing elements, How to find, in basic and complex array, triplet elements, whose sum matches or equals to any given target number, Finding in sorted & unsorted basic and complex arrays, two (2) elements whose sum equals to any given target number, Moving all zero values to the right in basic and complex arrays. These are just to summarise a few of the topics in this book. It also uses one of the world’s most popular programming languages (C# – pronounced C-Sharp) to describe how it can be applied or implemented by beginners, developers, and novices alike, for real-life scenario solutions, and it includes comprehensive asynchronous C# implementation and Test code, with useful reference points. Note: All C# code is written as asynchronous code. The book also offers the opportunity to learn asynchronous task process implementation methods in C#.

This book not only serves as a first-hand personal reference guide, for anyone that may need it, or has to tackle solution/s involving array data structure algorithms, but is also useful for novices, beginners, and software developers. It provides a comprehensive list, and down-to-earth step-by-step algorithms, of how to handle, time complexity with arrays, and how to learn and write asynchronous task process programming in C#, and how to turn them into viable implementable real-life solutions.

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3. Algorithms C#: Explains Algorithms with Beautiful Pictures Learn it Easy Better and Well

This book is rich in examples, with beautiful pictures and texts, and explains the data structure and algorithms in a way that is easy to understand. It is designed to help programmers better use the energy of algorithms in daily projects.

• Classic reference book in the field of algorithms: reflects the core knowledge system of algorithms
• Comprehensive content: Comprehensive discussion of sorting, linked list, search, hash, graph, and tree algorithms, and data structures, covering the algorithms commonly used by every programmer
• The new C# implementation code, using a modular programming style, gives the actual code of the algorithm.

Simple is the beginning of wisdom. From the essence of the practice, this book to briefly explains the concept and vividly cultivates programming interest, you will learn it easily, fast, and well.

Buy This Book: https://amzn.to/3iQg9XY

4. Problem-Solving in Data Structures & Algorithms Using C#

This book is designed for interviews so, in Chapter 0, various preparation plans are proposed. Then in Chapter 1, a brief introduction of the programming language and the concept of recursion is explained. A number of problems based on recursion and array are explained.

• Then in the coming chapter, we will be looking into complexity analysis. Then we will be looking into Sorting & Searching techniques.
• Then will look into the various data structures and their algorithms. We will be looking into a Linked List, Stack, Queue, Trees, Heap, Hash Table, and Graphs.
• Then we will be looking into algorithm analysis, we will be looking into Brute Force algorithms, Greedy algorithms, Divide & Conquer algorithms, Dynamic Programming, and Backtracking.
• In the end, we will be looking into System Design, which will give a systematic approach to solving the design problems in an Interview.

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5. Data Structures and Algorithms in C#

The data structure is a way to represent the storage and organization of data in the computer for programming languages to easily access the data and process the data within. There are several kinds of data structures that are very commonly used: Array, List, Queue, Stack, Binary Tree, and Set which we will discuss here. The different data structure has their own characteristics. These data structures are used in most programming languages. Here we will use the C# language to represent those data structures and see how to use them.

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Here, in this article, I provided the list of Most Recommended Data Structure and Algorithms Books using C# Language for Beginners and Professionals and I hope this Most Recommended Data Structure and Algorithms Books for Beginners and Professional article will help you with your needs and you enjoy this Most Recommended Data Structure and Algorithms Books using C# Programming Language for Beginners and Professional article.

Problem Solving in Data Structures & Algorithms Using C# Problem Solving in Data Structures & Algorithms Using C#

Title availability, subject and genre.

• C# (Computer program language)
• Computer algorithms.
• Data structures (Computer science)
• [Place of publication not identified] : Hemant Jain, [2016]

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Home » .Net » C# Programs

C# Data Structure Programs

Learn and practice the data structures problems on arrays, sorting, searching, stacks, queues, dequeues, hashes, etc. with solved C# programs/examples.

List of C# Data Structure Programs

• C# program to implement stack using array
• C# program to implement stack using structure
• C# program to implement Double Stack using structure
• C# program to implement Double Stack using class
• C# program to implement linear queue using array
• C# program to implement Linear Queue using structure
• C# program to implement circular queue using array
• C# program to implement the Circular Queue using structure
• C# program to push elements to stack using collection
• C# program to pop elements from stack using collection
• C# program to peek elements from stack using collection
• C# program to clear all elements from stack
• C# program to check whether element exists in stack or not
• C# program to get total number of elements in stack
• C# program to copy stack elements to array
• C# program to insert or enqueue elements into queue using collection
• C# program to delete or dequeue elements from queue using collection
• C# program to clear all elements of Queue
• C# program to count total items/elements of Queue
• C# program to check element is exist in Queue or not
• C# program to copy Queue elements to array
• C# program to convert queue into object array
• C# program to peek elements from Queue using collection
• C# program to implement In-order traversal in Binary Tree
• C# program to implement Pre-order traversal in Binary Tree
• C# program to implement Post-order traversal in Binary Tree
• C# program to get all stack frames using StackTrace class
• C# program to traverse the singly linked list
• C# program to delete a given node from the singly Linked-List
• C# program to demonstrate the Tower Of Hanoi
• C# program to implement selection Sort
• C# program to implement selection Sort to arrange elements in the descending order
• C# program to sort an array in ascending order using insertion sort
• C# program to sort an array in descending order using insertion sort
• C# program to sort an array in ascending order using bubble sort
• C# program to sort an array in descending order using bubble sort
• C# program to sort an array using quick sort
• C# program to sort an array using merge sort
• C# program to sort an integer array using Radix Sort
• C# program to implement the Heap Sort

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Data Structures

Arrays - ds easy problem solving (basic) max score: 10 success rate: 93.18%, 2d array - ds easy problem solving (basic) max score: 15 success rate: 93.15%, dynamic array easy problem solving (basic) max score: 15 success rate: 86.87%, left rotation easy problem solving (basic) max score: 20 success rate: 91.32%, sparse arrays medium problem solving (basic) max score: 25 success rate: 97.28%, array manipulation hard problem solving (intermediate) max score: 60 success rate: 61.39%, print the elements of a linked list easy problem solving (basic) max score: 5 success rate: 97.16%, insert a node at the tail of a linked list easy problem solving (intermediate) max score: 5 success rate: 95.27%, insert a node at the head of a linked list easy problem solving (basic) max score: 5 success rate: 98.32%, insert a node at a specific position in a linked list easy problem solving (intermediate) max score: 5 success rate: 96.97%, cookie support is required to access hackerrank.

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This is the code repository of book "Problem Solving in Data Structures & Algorithms Using C".

About The Book

• This textbook provides in depth coverage of various Data Structures and Algorithms.
• Concepts are discussed in easy to understand manner.
• Large number of diagrams are provided to grasp concepts easily.
• Time and Space complexities of various algorithms are discussed.
• Helpful for interviews preparation and competitive coding.
• Large number of interview questions are solved.
• C solutions are provided with input and output.
• Guide you through how to solve new problems in programming interview of various software companies.

Table of Contents

• Chapter 0: How to use this book.
• Chapter 1: Algorithms Analysis
• Chapter 2: Approach to solve algorithm design problems
• Chapter 3: Abstract Data Type
• Chapter 4: Searching
• Chapter 5: Sorting
• Chapter 6: Linked List
• Chapter 7: Stack
• Chapter 8: Queue
• Chapter 9: Tree
• Chapter 10: Priority Queue
• Chapter 11: Hash-Table
• Chapter 12: Graphs
• Chapter 13: String Algorithms
• Chapter 14: Algorithm Design Techniques
• Chapter 15: Brute Force Algorithm
• Chapter 16: Greedy Algorithm
• Chapter 17: Divide & Conquer
• Chapter 18: Dynamic Programming
• Chapter 19: Backtracking
• Chapter 20: Complexity Theory
• Python 1.7%

• Computers & Technology
• Programming

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Data Structures and Algorithms Using C# 1st Edition

Purchase options and add-ons.

• ISBN-10 0521670152
• ISBN-13 978-0521670159
• Edition 1st
• Publisher Cambridge University Press
• Publication date April 26, 2007
• Language English
• Dimensions 7 x 0.83 x 9.25 inches
• Print length 366 pages
• See all details

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• Publisher ‏ : ‎ Cambridge University Press; 1st edition (April 26, 2007)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 366 pages
• ISBN-10 ‏ : ‎ 0521670152
• ISBN-13 ‏ : ‎ 978-0521670159
• Item Weight ‏ : ‎ 1.52 pounds
• Dimensions ‏ : ‎ 7 x 0.83 x 9.25 inches
• #12 in Data Structure and Algorithms
• #52 in C# Programming (Books)
• #924 in Computer Software (Books)

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