# Crack the top 45 C# data structure questions

Mar 09, 2021 - 23 min read Ryan Thelin  Data structure questions are some of the most commonly asked in coding interviews. These questions test your ability to implement, optimize, and adapt data structures to solve a unique situation. It’s essential to review common questions before your coding interview to ensure you’re not caught off guard with an unfamiliar question.

Today, we’ll help you brush up on your data structure skills by reviewing 45 of the top data structure questions you should practice before your next interview.

Here’s what we’ll cover today:

## Complexity Measures Questions

### 1. Big O complexity: Nested Addition

Find the Big O complexity of the following code snippet.

using System;
namespace Chapter_1
{
class Challenge_1
{
static void Main(string[] args)
{
int n = 10;
int sum = 0;
float pie = 3.14F;
for (int i = 0; i < n; i += 3)
{
Console.WriteLine(pie);
for (int j = 0; j < n; j += 2)
{
sum += 1;
Console.WriteLine(sum);
}
}
}
}
}

### 2. Big O complexity: Nested Multiplication

Find the Big O complexity of the following code snippet.

using System;
namespace Chapter_1
{
class Challenge_6
{
static void Main(string[] args)
{
int n = 10;
int sum = 0;
float pie = 3.14f;
for (int i = 0; i < n; i++)
{
int j = 1;
Console.WriteLine(pie);
while (j < i)
{
sum += 1;
j *= 2;
}
}
Console.WriteLine(sum);

return;
}
}
}

### 3. Big O with nested multiplication (advanced)

Find the Big O complexity of the following code snippet:

using System;
namespace Chapter_1
{
class Challenge_7
{
static void Main(string[] args)
{
int n = 10;    // you can change the value of n
int sum = 0;
int j = 1;
float pie = 3.14f;
for (int i = 0; i < n; i++)
{
Console.WriteLine(pie);
while (j < i)
{
sum += 1;
j *= 2;
}
}
Console.WriteLine(sum );
}
}
}

## C# Arrays

### 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:

// Input: Arr = [1,2,4,5,10,6,3]
// Output: Arr = [1,5,3]

Solution and Explanation

using System;
namespace chapter_2
{
class Solution
{
static int [] removeEven(int[]Arr, int size)
{
int m = 0;
for (int i = 0; i < size; i++)
{
if (Arr[i] % 2 != 0)  // if odd number found
{
Arr[m] = Arr[i];   //inserting odd values in the array
++m;
}
}
int[] temp = new int[m];
for (int i = 0; i < m; i++)
temp[i] = Arr[i];

Arr = temp;
return Arr;  // returning the array after removing the odd numbers
}
//Remove Event Integers from an Array:
static void Main(string[] args)
{
int[] arr = null;      // declaring array
arr = new int;   // memory allocation
Console.Write("Before remove even: ");
for (int i = 0; i < 10; i++)
{
arr[i] = i;      // assigning values
Console.Write(arr[i] + " ");
}
Console.WriteLine("");
arr = removeEven(arr, 10);   // calling removeEven
Console.Write("After remove even: ");
for (int i = 0; i < 5; i++)
{
Console.Write( arr[i] + " ");    // prinitng array
}
Console.WriteLine("");
return ;
}

}
}

Time Complexity: $O(n)$

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.

For example:

// Input: arr = [9,2,3,6]
// Output: 2


Solution and Explanation

using System;
namespace chapter_2
{
class Solution
{
// Find Minimum Value in an Array
static int findMinimum(int []arr, int size)
{
int minimum = arr;

//At every index compare its value with the minimum and if it is less
//then make that index value the new minimum value”

for (int i = 0; i < size; i++)
{

if (arr[i] < minimum)
{
minimum = arr[i];
}
}
return minimum;
}
static void Main(string[] args)
{
int size = 4;
int []arr = { 9, 2, 3, 6 };
Console.Write("Array : ");
for (int i = 0; i < size; i++)
Console.Write(arr[i] + " ");

Console.WriteLine("");
int min = findMinimum(arr, size);
Console.WriteLine("Minimum in the Array: " + min );

return ;
}
}
}

Time Complexity: $O(n)$

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.

Solution and Explanation

using System;

namespace chapter_2
{
class Solution
{
//Maximum Sum Subarray
static int maxSumArr(int []arr, int arrSize)
{
if (arrSize < 1)
{
return 0;
}

int currMax = arr;
int globalMax = arr;

for (int i = 1; i < arrSize; i++)
{
if (currMax < 0)
{
currMax = arr[i];
}
else
{
currMax += arr[i];
}

if (globalMax < currMax)
{
globalMax = currMax;
}
}
return globalMax;
}

static void Main(string[] args)
{
int []arr = { -4, 2, -5, 1, 2, 3, 6, -5, 1 };
int arrSize = arr.Length;
int maxSum = maxSumArr(arr, arrSize);
Console.WriteLine("Maximum contiguous sum is " + maxSum);
return;
}

}
}

Time Complexity: $O(n)$

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

Take a look at Kadane’s algorithm in pseudocode:

currMax = A
globalMax = A
for i = 1 -> size of A
if currMax is less than 0
then currMax = A[i]
otherwise
currMax = currMax + A[i]
if globalMax is less than currMax
then globalMax = currMax


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:

using System;

{
public class Node
{
internal int data; //Data to store (could be int,string,object etc)
internal Node nextElement; //Pointer to next element

public Node()
{
//Constructor to initialize nextElement of newlyCreated Node
nextElement = null;
}
};

{
}
public bool IsEmpty()
{
return true;
else
return false;
}
//Function inserts a value/new Node as the first Element of list
{
Node newNode = new Node(); //creating a new node
newNode.data = value;
Console.Write(value + " Inserted !    ");
}
public bool PrintList()
{        // Printing the list
if (IsEmpty())
{
Console.Write("List is Empty!");
return false;
}
Console.Write("List : ");

while (temp != null)
{     // traveresing through the List
Console.Write(temp.data + "->");
temp = temp.nextElement;    // moving on to the temp's nextElement
}
Console.WriteLine("null ");    // printing null at the end
return true;
}
}


### 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.

Solution and Explanation

main.cs
using System;
namespace chapter_3
{
{
public class Node
{
internal int data; //Data to store (could be int,string,object etc)
internal Node nextElement; //Pointer to next element

public Node()
{
//Constructor to initialize nextElement of newlyCreated Node
nextElement = null;
}
};

{
}
{
}
bool IsEmpty()
{
return true;
else
return false;
}
public bool PrintList()
{
if (IsEmpty())
{
Console.Write("List is Empty!");
return false;
}
Console.Write("List : ");

while (temp != null)
{
Console.Write(temp.data + "->");
temp = temp.nextElement;
}
Console.WriteLine("null ");
return true;
}
{
Node newNode = new Node();
newNode.data = value;

}
public string Elements()
{
string elementsList = "";

while (start != null)
{
elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;
}
elementsList += "null";
return elementsList;
}
public void InsertAtTail(int value)
{
if (IsEmpty())
{ // inserting first element in list
}
else
{
Node newNode = new Node(); // creating new node
Node last = head; // last pointing at the head of the list

while (last.nextElement != null)
{ // traversing through the list
last = last.nextElement;
}

newNode.data = value;
Console.Write(value + " Inserted!    ");
newNode.nextElement = null; // point last's nextElement to nullptr
last.nextElement = newNode; // adding the newNode at the end of the list
}
}
}
}

Time Complexity: $O(n)$

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.

Solution and Explanation

main.cs
using System;
namespace chapter_3
{
{
public class Node
{
internal int data; //Data to store (could be int,string,object etc)
internal Node nextElement; //Pointer to next element

public Node()
{
//Constructor to initialize nextElement of newlyCreated Node
nextElement = null;
}
};

{
}
{
}
bool IsEmpty()
{
return true;
else
return false;
}
public bool PrintList()
{
if (IsEmpty())
{
Console.Write("List is Empty!");
return false;
}
Console.Write("List : ");

while (temp != null)
{
Console.Write(temp.data + "->");
temp = temp.nextElement;
}
Console.WriteLine("null ");
return true;
}
{
Node newNode = new Node();
newNode.data = value;
Console.Write(value + " Inserted!");
}
public string Elements()
{ // this function will return all values of linked List
string elementsList = "";

elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;

while (start != null && start.data != check.data)
{
elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;
}

if (start == null)
return elementsList + "null";

elementsList += check.data.ToString();
return elementsList;
}

public string RemoveDuplicates()
{
Node start, startNext = null;

/* Pick elements one by one */
while ((start != null) && (start.nextElement != null))
{
startNext = start;

/* Compare the picked element with rest
of the elements */
while (startNext.nextElement != null)
{
/* If duplicate then delete it */
if (start.data == startNext.nextElement.data)
{

// skipping elements from the list to be deleted
startNext.nextElement = startNext.nextElement.nextElement;

}
else
startNext = startNext.nextElement; // pointing to next of startNext
}
start = start.nextElement;
}
return Elements();
}
}
}

Time Complexity: $O(n^2)$

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.

Solution and Explanation

main.cs
using System;
namespace chapter_3
{
{
public class Node
{
internal int data; //Data to store (could be int,string,object etc)
internal Node nextElement; //Pointer to next element

public Node()
{
//Constructor to initialize nextElement of newlyCreated Node
nextElement = null;
}
};

{
}
{
}
bool IsEmpty()
{
return true;
else
return false;
}
public bool PrintList()
{
if (IsEmpty())
{
Console.Write("List is Empty!");
return false;
}
Console.Write("List : ");

while (temp != null)
{
Console.Write(temp.data + "->");
temp = temp.nextElement;
}
Console.WriteLine("null ");
return true;
}
{
Node newNode = new Node();
newNode.data = value;

}
public string Elements()
{ // this function will return all values of linked List
string elementsList = "";

elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;

while (start != null && start.data != check.data)
{
elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;
}

if (start == null)
return elementsList + "null";

elementsList += check.data.ToString();
return elementsList;
}

public string RemoveDuplicates()
{
Node start, startNext = null;

/* Pick elements one by one */
while ((start != null) && (start.nextElement != null))
{
startNext = start;

/* Compare the picked element with rest
of the elements */
while (startNext.nextElement != null)
{
/* If duplicate then delete it */
if (start.data == startNext.nextElement.data)
{

// skipping elements from the list to be deleted
startNext.nextElement = startNext.nextElement.nextElement;

}
else
startNext = startNext.nextElement; // pointing to next of startNext
}
start = start.nextElement;
}
return Elements();

}
{
//Return other List if one of them is empty
if (list1.IsEmpty())
return list2.Elements();
else if (list2.IsEmpty())
return list1.Elements();

//Traverse first list till the last element
while (start.nextElement != null)
{
start = start.nextElement;
}

//Link last element of first list to the first element of second list
start.nextElement = list2.head; // appendinf list2 with list 1
return list1.RemoveDuplicates(); // removing duplicates from list and return list
}
}
}

Time Complexity: $O(m + n)^2$ 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.

## C# Stacks and Queues

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


using System;
using System.Diagnostics;

class myStack
{
int[] stackArr;
int capacity;
int numElements;

public myStack(int size)
{
capacity = size;
stackArr = new int[size];
Debug.Assert(stackArr != null);
numElements = 0;
}

public bool isEmpty()
{
return (numElements == 0);
}

public int getTop()
{
return (numElements == 0 ? -1 : stackArr[numElements - 1]);
}

public bool push(int value)
{
if (numElements < capacity)
{
stackArr[numElements] = value;
numElements++;
return true;
}
else
{
Console.WriteLine("Stack Full.");
return false;
}
}

public int pop()
{
if (numElements == 0)
{
Console.WriteLine("Stack Empty");
return -1;
}
else
{
numElements--;
return stackArr[numElements];
}
}

public int getSize()
{
return numElements;
}
public void showStack()
{
int i = 0;
while (i < numElements)
{
Console.Write("\t" + stackArr[numElements - 1 - i]);
i++;
}
Console.WriteLine("");
}
}

### 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.

Solution and Explanation

using System;
using System.Collections;
namespace chapter_4
{
class Challenge_1
{
//Dequeue a number from queue and append 0 to it and enqueue it back to queue.
//Perform step 2 but with appending 1 to the original number and enqueue back to queue.
//Queue takes integer values so before enqueueing it make sure to convert string to integer.
//Size of Queue should be 1 more than number because for a single number we're enqueuing two
//variations of it , one with appended 0 while other with 1 being appended.
static string [] findBin(int n)
{
string [] result = new string[n];
Queue queue = new Queue();
queue.Enqueue(1);
string s1, s2;
for (int i = 0; i < n; i++)
{
result[i] = queue.Dequeue().ToString();
s1 = result[i] + "0";
s2 = result[i] + "1";
queue.Enqueue(Convert.ToInt32(s1));
queue.Enqueue(Convert.ToInt32(s2));
}

return result;
}

static void Main(string[] args)
{
var output = findBin(4);
for (int i = 0; i < 4; i++)
Console.Write(output[i] + " ");

return;
}
}
}

Time Complexity: $O(n)$

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.

Solution and Explanation

using System;
using System.Collections.Generic;

namespace chapter_4
{
//Create Stack => myStack stack = new myStack(5);
//where 5 is size of stack
//Push Function => stack.push(int);
//Pop Function => stack.pop();
//TopFunction => stack.getTop();
//Helper Functions => stack.isEmpty();

class newQueue
{

Stack <int> mainStack;
Stack <int> tempStack;

public newQueue()
{
//Can use size from argument to create stack
mainStack = new Stack<int> ();
tempStack = new Stack<int> ();
}

void EnQueue(int value)
{
//Traverse elements from mainStack to tempStack
//Push given value to mainStack
//Traverse back the elements from tempStack to mainStack
while (mainStack.Count != 0)
{

tempStack.Push(mainStack.Pop());
}

mainStack.Push(value);

while (tempStack.Count != 0)
{

mainStack.Push(tempStack.Pop());
}

}
int DeQueue()
{
//If mainStack is empty then we have no elements.
//else return top element of mainStack as we always put oldest entered
//element at the top of mainStack
if (mainStack.Count == 0)
return -1;
else
return mainStack.Pop();
}
static void Main(string[] args)
{
newQueue queue = new newQueue();

queue.EnQueue(1);
queue.EnQueue(2);
queue.EnQueue(3);
queue.EnQueue(4);
queue.EnQueue(5);

Console.WriteLine( queue.DeQueue());
Console.WriteLine( queue.DeQueue());
Console.WriteLine( queue.DeQueue());
Console.WriteLine(queue.DeQueue());
Console.WriteLine( queue.DeQueue());
Console.WriteLine(queue.DeQueue());
return ;
}

};

}

Time Complexity: $O(n)$

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 $O(1)$.

Hint: The element is returned, not popped.

Solution and Explanation

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;

namespace chapter_4
{
class newStack
{

//We will use two stacks mainStack to hold origional values
//and minStack to hold minimum values. Top of minStack will always
//be the minimum value from mainStack
Stack <int> mainStack;
Stack<int> minStack;

public newStack(int size)
{
mainStack = new Stack<int>(size);
minStack = new Stack<int>(size);
}

//Removes and returns value from newStack
//1. Pop element from minStack to make it sync with mainStack.
//2. Pop element from mainStack and return that value.
int pop()
{

minStack.Pop();
return mainStack.Pop();

}

//Pushes values into newStack
//1. Push value in mainStack and check value with the top value of minStack
//2. If value is greater than top, then push top in minStack
//else push value in minStack.
void push(int value)
{

mainStack.Push(value);

if ( (minStack.Count != 0) && (value > minStack.Peek()) )
{
minStack.Push(minStack.Peek());
}
else
minStack.Push(value);
}

//Returns minimum value from newStack in O(1) Time
int min()
{
return minStack.Peek();
}
static void Main(string[] args)
{
newStack stack = new newStack(6);
stack.push(5);
stack.push(2);
stack.push(4);
stack.push(1);
stack.push(3);
stack.push(9);

Console.WriteLine(stack.min());
stack.pop();
stack.pop();
stack.pop();
Console.WriteLine(stack.min());

return ;
}
}
}

Time Complexity: $O(1)$

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.

## C# Graphs

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
main.cs
Graph.cs
using System;

namespace chapter_5
{
{
public class Node
{
internal int data; //Data to store (could be int,string,object etc)
internal Node nextElement; //Pointer to next element

public Node()
{
//Constructor to initialize nextElement of newlyCreated Node
nextElement = null;
}
};

{
}
{
}
bool IsEmpty()
{
return true;
else
return false;
}
public bool PrintList()
{
if (IsEmpty())
{
Console.Write("List is Empty!");
return false;
}
Console.Write("List : ");

while (temp != null)
{
Console.Write(temp.data + "->");
temp = temp.nextElement;
}
Console.WriteLine("null ");
return true;
}
{
Node newNode = new Node();
newNode.data = value;

}
public string Elements()
{ // this function will return all values of linked List
string elementsList = "";

elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;

while (start != null && start.data != check.data)
{
elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;
}

if (start == null)
return elementsList + "null";

elementsList += check.data.ToString();
return elementsList;
}
public void InsertAtTail(int value)
{
if (IsEmpty())
{ // inserting first element in list
}
else
{
Node newNode = new Node(); // creating new node
Node last = head; // last pointing at the head of the list

while (last.nextElement != null)
{ // traversing through the list
last = last.nextElement;
}

newNode.data = value;
Console.Write(value + " Inserted!    ");
newNode.nextElement = null; // point last's nextElement to nullptr
last.nextElement = newNode; // adding the newNode at the end of the list
}
}

// function to check if element exists in the list
public bool Search(int value)
{

while (temp != null)
{
if (temp.data == value)
{ // if passed value matches with temp's data
return true;
}
temp = temp.nextElement; // pointig to temp's nextElement
}
}

public bool Delete(int value)
{
bool deleted = false; //returns true if the node is deleted, false otherwise

if (IsEmpty())
{ //check if the list is empty
Console.WriteLine("List is Empty");
return deleted; //deleted will be false
}

//if list is not empty, start traversing it from the head
Node currentNode = head; //currentNode to traverse the list
Node previousNode = null; //previousNode starts from null

if (currentNode.data == value)
{ // deleting value of head
Console.WriteLine(value + " deleted!");
deleted = true; // true because value found and deleted
return deleted; //returns true if the node is deleted
}
previousNode = currentNode;
currentNode = currentNode.nextElement; // pointing current to current's nextElement
//Traversing/Searching for Node to Delete
while (currentNode != null)
{

//Node to delete is found
if (value == currentNode.data)
{
// pointing previousNode's nextElement to currentNode's nextElement
previousNode.nextElement = currentNode.nextElement;
// delete currentNode;
currentNode = previousNode.nextElement;
deleted = true;
break;
}
previousNode = currentNode;
currentNode = currentNode.nextElement; // pointing current to current's nextElement
}
//deleted is true only when value is found and deleted
if (deleted == false)
{
Console.WriteLine(value + " does not exist!");
}
else
{
Console.WriteLine(value + " deleted!");
}
return deleted;
} //end of delete()
{
if (IsEmpty())
{ // check if list is empty
Console.WriteLine("List is Empty");
return false;
}

return true;
}

public int Length()
{
Node current = head; // Start from the first element
int count = 0; // in start count is 0

while (current != null)
{ // Traverse the list and count the number of nodes
count++; // increment everytime as element is found
current = current.nextElement; // pointing to current's nextElement
}
return count;
}

public string Reverse()
{
Node previous = null; //To keep track of the previous element, will be used in swapping links
Node next = null;

//While Traversing the list, swap links
while (current != null)
{
next = current.nextElement;
current.nextElement = previous;
previous = current;
current = next;
}

return Elements(); // calling elements to return a string of values in list
}

public bool DetectLoop()
{

while ((slow != null) && (fast != null) && (fast.nextElement != null)) //checking if all elements exist
{
slow = slow.nextElement;
fast = fast.nextElement.nextElement;

/* If slow and fast meet at some point then there
is a loop */
if (slow == fast)
{
// Return 1 to indicate that loop is found */
return true;
}
}
// Return 0 to indicate that ther is no loop*/
return false;
}
public void InsertLoop()
{
// traversing to get to last element of the list
while (temp.nextElement != null)
{
temp = temp.nextElement;
}
temp.nextElement = head; // pointing last element to head of the list
}

public int FindMid()
{
//list is empty
if (IsEmpty())
return 0;

if (currentNode.nextElement == null)
{
//Only 1 element exist in array so return its value.
return currentNode.data;
}

Node midNode = currentNode; //midNode starts at head
currentNode = currentNode.nextElement.nextElement; //currentNode moves two steps forward

//Move midNode (Slower) one step at a time
//Move currentNode (Faster) two steps at a time
//When currentNode reaches at end, midNode will be at the middle of List
while (currentNode != null)
{       // traversing from head to end

midNode = midNode.nextElement;

currentNode = currentNode.nextElement;     // pointing to current's next
if (currentNode != null)
currentNode = currentNode.nextElement;     // pointing to current's next

}
if (midNode != null)     // pointing at middle of the list
return midNode.data;
return 0;
}

public string RemoveDuplicates()
{
Node start, startNext = null;

/* Pick elements one by one */
while ((start != null) && (start.nextElement != null))
{
startNext = start;

/* Compare the picked element with rest
of the elements */
while (startNext.nextElement != null)
{
/* If duplicate then delete it */
if (start.data == startNext.nextElement.data)
{

// skipping elements from the list to be deleted
startNext.nextElement = startNext.nextElement.nextElement;

}
else
startNext = startNext.nextElement; // pointing to next of startNext
}
start = start.nextElement;
}
return Elements();

}

{
//Return other List if one of them is empty
if (list1.IsEmpty())
return list2.Elements();
else if (list2.IsEmpty())
return list1.Elements();

//Traverse first list till the last element
while (start.nextElement != null)
{
start = start.nextElement;
}

//Link last element of first list to the first element of second list
start.nextElement = list2.head; // appendinf list2 with list 1
return list1.RemoveDuplicates(); // removing duplicates from list and return list
}

//To Find nth node from end of list
public int FindNth(int n)
{

if (IsEmpty()) // if list is empty return -1
return -1;

int length = 0;

// finding the length of the list
while (currentNode != null)
{
currentNode = currentNode.nextElement;
length++;
}

//Find the Node which is at (len - n) position from start
int position = length - n;

if (position < 0 || position > length) // check if out of the range of the list
return -1;

int count = 0;
// traversing till the nth Element of the list
while (count != position)
{ // finding the position of the element
currentNode = currentNode.nextElement;
count++;
}

if (currentNode != null) // if node exists
return currentNode.data;

return -1;

}
}

}

### 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.

Solution and Explanation

main.cs
Graph.cs
using System;
using System.Collections.Generic;

namespace chapter_5
{
class Challenge_2
{
static void dfs_helper(Graph g, int source, bool [] visited, ref string result)
{
if (g.getVertices() < 1)
{
return;
}

//Create Stack(Implemented in previous chapters) for Depth First Traversal and Push source in it
Stack<int> stack = new Stack<int> { };

stack.Push(source);
visited[source] = true;
int current_node;
//Traverse while stack is not empty
while (stack.Count != 0)
{

//Pop a vertex/node from stack and add it to the result
current_node = stack.Pop();
result += current_node.ToString() ;

//Get adjacent vertices to the current_node from the array,
//and if they are not already visited then push them in the stack

while (temp != null)
{

if (!visited[temp.data])
{
stack.Push(temp.data);
//Visit the node
visited[temp.data] = true;
}
temp = temp.nextElement;
}
} //end of while

}
static string dfsTraversal(Graph g)
{
string result = "";

//Bool Array to hold the history of visited nodes
//Make a node visited whenever you push it into stack
bool [] visited = new bool[g.getVertices()];
for (int i = 0; i < g.getVertices(); i++)
{
visited[i] = false;
}
for (int i = 0; i < g.getVertices(); i++)
{
if (!visited[i])
dfs_helper(g, i, visited, ref result);
}

//delete[] visited;
visited = null;

return result;
}
static void Main(string[] args)
{
Graph g = new Graph(7);

Console.WriteLine (dfsTraversal(g));

}
}
}

Time Complexity: $O(V + N)$

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.

Solution and Explanation

main.cs
Graph.cs
using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.Remoting.Messaging;
using System.Text;

namespace chapter_5
{
class Graph
{
int vertices;

public Graph(int v)
{
vertices = v;
for(int i = 0; i < v; i++)
{
}
}

public void addEdge(int source, int destination)
{
if (source < vertices && destination < vertices)
}

public void printGraph()
{
for (int i = 0; i < vertices; i++)
{
Console.Write( "|" + i + "| => ");

while (temp != null)
{
Console.Write("[" + temp.data + "] -> ");
temp = temp.nextElement;
}
Console.WriteLine("NULL");
}
}

{
return array;
}

public int getVertices()
{
return vertices;
}
}
}

Time Complexity: $O(V + E)$

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.

Before and After remove_Edge()

Solution and Explanation

main.cs
Graph.cs
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;

namespace chapter_5
{
{
public class Node
{
internal int data; //Data to store (could be int,string,object etc)
internal Node nextElement; //Pointer to next element

public Node()
{
//Constructor to initialize nextElement of newlyCreated Node
nextElement = null;
}
};

{
}
{
}
bool IsEmpty()
{
return true;
else
return false;
}
public bool PrintList()
{
if (IsEmpty())
{
Console.Write("List is Empty!");
return false;
}
Console.Write("List : ");

while (temp != null)
{
Console.Write(temp.data + "->");
temp = temp.nextElement;
}
Console.WriteLine("null ");
return true;
}
{
Node newNode = new Node();
newNode.data = value;

}
public string Elements()
{ // this function will return all values of linked List
string elementsList = "";

elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;

while (start != null && start.data != check.data)
{
elementsList += start.data.ToString();
elementsList += "->";
start = start.nextElement;
}

if (start == null)
return elementsList + "null";

elementsList += check.data.ToString();
return elementsList;
}
public void InsertAtTail(int value)
{
if (IsEmpty())
{ // inserting first element in list
}
else
{
Node newNode = new Node(); // creating new node
Node last = head; // last pointing at the head of the list

while (last.nextElement != null)
{ // traversing through the list
last = last.nextElement;
}

newNode.data = value;
Console.Write(value + " Inserted!    ");
newNode.nextElement = null; // point last's nextElement to nullptr
last.nextElement = newNode; // adding the newNode at the end of the list
}
}

// function to check if element exists in the list
public bool Search(int value)
{

while (temp != null)
{
if (temp.data == value)
{ // if passed value matches with temp's data
return true;
}
temp = temp.nextElement; // pointig to temp's nextElement
}
}

public bool Delete(int value)
{
bool deleted = false; //returns true if the node is deleted, false otherwise

if (IsEmpty())
{ //check if the list is empty
Console.WriteLine("List is Empty");
return deleted; //deleted will be false
}

//if list is not empty, start traversing it from the head
Node currentNode = head; //currentNode to traverse the list
Node previousNode = null; //previousNode starts from null

if (currentNode.data == value)
{ // deleting value of head
Console.WriteLine(value + " deleted!");
deleted = true; // true because value found and deleted
return deleted; //returns true if the node is deleted
}
previousNode = currentNode;
currentNode = currentNode.nextElement; // pointing current to current's nextElement
//Traversing/Searching for Node to Delete
while (currentNode != null)
{

//Node to delete is found
if (value == currentNode.data)
{
// pointing previousNode's nextElement to currentNode's nextElement
previousNode.nextElement = currentNode.nextElement;
// delete currentNode;
currentNode = previousNode.nextElement;
deleted = true;
break;
}
previousNode = currentNode;
currentNode = currentNode.nextElement; // pointing current to current's nextElement
}
//deleted is true only when value is found and deleted
if (deleted == false)
{
Console.WriteLine(value + " does not exist!");
}
else
{
Console.WriteLine(value + " deleted!");
}
return deleted;
} //end of delete()
{
if (IsEmpty())
{ // check if list is empty
Console.WriteLine("List is Empty");
return false;
}

return true;
}

public int Length()
{
Node current = head; // Start from the first element
int count = 0; // in start count is 0

while (current != null)
{ // Traverse the list and count the number of nodes
count++; // increment everytime as element is found
current = current.nextElement; // pointing to current's nextElement
}
return count;
}

public string Reverse()
{
Node previous = null; //To keep track of the previous element, will be used in swapping links
Node next = null;

//While Traversing the list, swap links
while (current != null)
{
next = current.nextElement;
current.nextElement = previous;
previous = current;
current = next;
}

return Elements(); // calling elements to return a string of values in list
}

public bool DetectLoop()
{

while ((slow != null) && (fast != null) && (fast.nextElement != null)) //checking if all elements exist
{
slow = slow.nextElement;
fast = fast.nextElement.nextElement;

/* If slow and fast meet at some point then there
is a loop */
if (slow == fast)
{
// Return 1 to indicate that loop is found */
return true;
}
}
// Return 0 to indeciate that ther is no loop*/
return false;
}
public void InsertLoop()
{
// traversing to get to last element of the list
while (temp.nextElement != null)
{
temp = temp.nextElement;
}
temp.nextElement = head; // pointing last element to head of the list
}

public int FindMid()
{
//list is empty
if (IsEmpty())
return 0;

if (currentNode.nextElement == null)
{
//Only 1 element exist in array so return its value.
return currentNode.data;
}

Node midNode = currentNode; //midNode starts at head
currentNode = currentNode.nextElement.nextElement; //currentNode moves two steps forward

//Move midNode (Slower) one step at a time
//Move currentNode (Faster) two steps at a time
//When currentNode reaches at end, midNode will be at the middle of List
while (currentNode != null)
{       // traversing from head to end

midNode = midNode.nextElement;

currentNode = currentNode.nextElement;     // pointing to current's next
if (currentNode != null)
currentNode = currentNode.nextElement;     // pointing to current's next

}
if (midNode != null)     // pointing at middle of the list
return midNode.data;
return 0;
}

public string RemoveDuplicates()
{
Node start, startNext = null;

/* Pick elements one by one */
while ((start != null) && (start.nextElement != null))
{
startNext = start;

/* Compare the picked element with rest
of the elements */
while (startNext.nextElement != null)
{
/* If duplicate then delete it */
if (start.data == startNext.nextElement.data)
{

// skipping elements from the list to be deleted
startNext.nextElement = startNext.nextElement.nextElement;

}
else
startNext = startNext.nextElement; // pointing to next of startNext
}
start = start.nextElement;
}
return Elements();

}

{
//Return other List if one of them is empty
if (list1.IsEmpty())
return list2.Elements();
else if (list2.IsEmpty())
return list1.Elements();

//Traverse first list till the last element
while (start.nextElement != null)
{
start = start.nextElement;
}

//Link last element of first list to the first element of second list
start.nextElement = list2.head; // appendinf list2 with list 1
return list1.RemoveDuplicates(); // removing duplicates from list and return list
}

//To Find nth node from end of list
public int FindNth(int n)
{

if (IsEmpty()) // if list is empty return -1
return -1;

int length = 0;

// finding the length of the list
while (currentNode != null)
{
currentNode = currentNode.nextElement;
length++;
}

//Find the Node which is at (len - n) position from start
int position = length - n;

if (position < 0 || position > length) // check if out of the range of the list
return -1;

int count = 0;
// traversing till the nth Element of the list
while (count != position)
{ // finding the position of the element
currentNode = currentNode.nextElement;
count++;
}

if (currentNode != null) // if node exists
return currentNode.data;

return -1;

}
}
}

Time Complexity: $O(E)$

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 and3.

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#

## C# Trees and Tries

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

main.cs
BST.cs
namespace chapter_6
{
// Node class with a value, left child node, and the rithe child node
class Node
{
public int value;
public Node leftChild;
public Node rightChild;
public Node()
{
value = 0;
leftChild = null;
rightChild = null;
}

public Node(int val)
{
value = val;
leftChild = null;
rightChild = null;
}
};
//BinarySearchTree class that contains the root node.
class BinarySearchTree
{
Node root;
public BinarySearchTree(int rootValue)
{
root = new Node(rootValue);
}
public BinarySearchTree()
{
root = null;
}
public Node getRoot()
{
return root;
}
};
}

### 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.

Solution and Explanation

main.cs
BST.cs
using System;

namespace chapter_6
{
class Node
{
public int value;
public Node leftChild;
public Node rightChild;
public Node()
{
value = 0;
leftChild = null;
rightChild = null;
}

public Node(int val)
{
value = val;
leftChild = null;
rightChild = null;
}
}
class BinarySearchTree
{
Node root;
public BinarySearchTree(int rootValue)
{
root = new Node(rootValue);
}
public BinarySearchTree()
{
root = null;
}
public Node getRoot()
{
return root;
}
public Node insert(Node currentNode, int val)
{
if (currentNode == null)
{
return new Node(val);
}
else if (currentNode.value > val)
{

currentNode.leftChild = insert(currentNode.leftChild, val);

}
else
{
currentNode.rightChild = insert(currentNode.rightChild, val);
}

return currentNode;

}

public void insertBST(int value)
{

if (getRoot() == null)
{
root = new Node(value);
return;
}
insert(this.getRoot(), value);
}

public void inOrderPrint(Node currentNode)
{
if (currentNode != null)
{
inOrderPrint(currentNode.leftChild);
Console.WriteLine(currentNode.value);
inOrderPrint(currentNode.rightChild);
}
}
Node searchBST(int value)
{

Node currentNode = root;
while ((currentNode != null) && (currentNode.value != value))
{
//the loop will run until the currentNode IS NOT null
//and until we get to our value
if (value < currentNode.value)
{
//traverse to the left subtree
currentNode = currentNode.leftChild;
}
else
{ //traverse to the right subtree
currentNode = currentNode.rightChild;

}

}
//after the loop, we'll have either the searched value
return currentNode;
}
public Node search(Node currentNode, int value)
{
if (currentNode == null)
return null;
else if (currentNode.value == value)
return currentNode;
else if (currentNode.value > value)
return search(currentNode.leftChild, value);
else
return search(currentNode.rightChild, value);
}

public bool deleteBST(int value)
{
return Delete(root, value);
}
public bool Delete(Node currentNode, int value)
{

if (root == null)
{
return false;
}

Node parent = root; //To Store parent of currentNode
while ((currentNode != null) && (currentNode.value != value))
{
parent = currentNode;
if (currentNode.value > value)
currentNode = currentNode.leftChild;
else
currentNode = currentNode.rightChild;

}

if (currentNode == null)
return false;
else if ((currentNode.leftChild == null) && (currentNode.rightChild == null))
{
//1. Node is Leaf Node
//if that leaf node is the root (a tree with just root)
if (root.value == currentNode.value)
{

root = null;
return true;
}
else if (currentNode.value < parent.value)
{

parent.leftChild = null;
return true;
}
else
{

parent.rightChild = null;
return true;
}

}
else if (currentNode.rightChild == null)
{

if (root.value == currentNode.value)
{

root = currentNode.leftChild;
return true;
}
else if (currentNode.value < parent.value)
{

parent.leftChild = currentNode.leftChild;
return true;
}
else
{

parent.rightChild = currentNode.leftChild;
return true;
}

}
else if (currentNode.leftChild == null)
{
if (root.value == currentNode.value)
{

root = currentNode.rightChild;
return true;
}
else if (currentNode.value < parent.value)
{

parent.leftChild = currentNode.rightChild;
return true;
}
else
{

parent.rightChild = currentNode.rightChild;
return true;
}

}
else
{
//Find Least Value Node in right-subtree of current Node
Node leastNode = findLeastNode(currentNode.rightChild);
//Set CurrentNode's Data to the least value in its right-subtree
int tmp = leastNode.value;
Delete(root, tmp);
currentNode.value = leastNode.value;
//Delete the leafNode which had the least value

return true;
}

}

//Helper function to find least value node in right-subtree of currentNode
public Node findLeastNode(Node currentNode)
{

Node temp = currentNode;

while (temp.leftChild != null)
{
temp = temp.leftChild;
}

return temp;

}
public void preOrderPrint(Node currentNode)
{
if (currentNode != null)
{
Console.WriteLine(currentNode.value);
preOrderPrint(currentNode.leftChild);
preOrderPrint(currentNode.rightChild);
}

}

}
}

Time Complexity: $O(h)$

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.

Example BST of height 3

Solution and Explanation

main.cs
BST.cs
using System;

namespace chapter_6
{
class Node
{
public int value;
public Node leftChild;
public Node rightChild;
public Node()
{
value = 0;
leftChild = null;
rightChild = null;
}

public Node(int val)
{
value = val;
leftChild = null;
rightChild = null;
}
}
class BinarySearchTree
{
Node root;
public BinarySearchTree(int rootValue)
{
root = new Node(rootValue);
}
public BinarySearchTree()
{
root = null;
}
public Node getRoot()
{
return root;
}
public Node insert(Node currentNode, int val)
{
if (currentNode == null)
{
return new Node(val);
}
else if (currentNode.value > val)
{

currentNode.leftChild = insert(currentNode.leftChild, val);

}
else
{
currentNode.rightChild = insert(currentNode.rightChild, val);
}

return currentNode;

}

public void insertBST(int value)
{

if (getRoot() == null)
{
root = new Node(value);
return;
}
insert(this.getRoot(), value);
}

public void inOrderPrint(Node currentNode)
{
if (currentNode != null)
{
inOrderPrint(currentNode.leftChild);
Console.WriteLine(currentNode.value);
inOrderPrint(currentNode.rightChild);
}
}
Node searchBST(int value)
{

Node currentNode = root;
while ((currentNode != null) && (currentNode.value != value))
{
//the loop will run until the currentNode IS NOT null
//and until we get to our value
if (value < currentNode.value)
{
//traverse to the left subtree
currentNode = currentNode.leftChild;
}
else
{ //traverse to the right subtree
currentNode = currentNode.rightChild;

}

}
//after the loop, we'll have either the searched value
return currentNode;
}
public Node search(Node currentNode, int value)
{
if (currentNode == null)
return null;
else if (currentNode.value == value)
return currentNode;
else if (currentNode.value > value)
return search(currentNode.leftChild, value);
else
return search(currentNode.rightChild, value);
}

public bool deleteBST(int value)
{
return Delete(root, value);
}
public bool Delete(Node currentNode, int value)
{

if (root == null)
{
return false;
}

Node parent = root; //To Store parent of currentNode
while ((currentNode != null) && (currentNode.value != value))
{
parent = currentNode;
if (currentNode.value > value)
currentNode = currentNode.leftChild;
else
currentNode = currentNode.rightChild;

}

if (currentNode == null)
return false;
else if ((currentNode.leftChild == null) && (currentNode.rightChild == null))
{
//1. Node is Leaf Node
//if that leaf node is the root (a tree with just root)
if (root.value == currentNode.value)
{

root = null;
return true;
}
else if (currentNode.value < parent.value)
{

parent.leftChild = null;
return true;
}
else
{

parent.rightChild = null;
return true;
}

}
else if (currentNode.rightChild == null)
{

if (root.value == currentNode.value)
{

root = currentNode.leftChild;
return true;
}
else if (currentNode.value < parent.value)
{

parent.leftChild = currentNode.leftChild;
return true;
}
else
{

parent.rightChild = currentNode.leftChild;
return true;
}

}
else if (currentNode.leftChild == null)
{
if (root.value == currentNode.value)
{

root = currentNode.rightChild;
return true;
}
else if (currentNode.value < parent.value)
{

parent.leftChild = currentNode.rightChild;
return true;
}
else
{

parent.rightChild = currentNode.rightChild;
return true;
}

}
else
{
//Find Least Value Node in right-subtree of current Node
Node leastNode = findLeastNode(currentNode.rightChild);
//Set CurrentNode's Data to the least value in its right-subtree
int tmp = leastNode.value;
Delete(root, tmp);
currentNode.value = leastNode.value;
//Delete the leafNode which had the least value

return true;
}

}

//Helper function to find least value node in right-subtree of currentNode
public Node findLeastNode(Node currentNode)
{

Node temp = currentNode;

while (temp.leftChild != null)
{
temp = temp.leftChild;
}

return temp;

}
public void preOrderPrint(Node currentNode)
{
if (currentNode != null)
{
Console.WriteLine(currentNode.value);
preOrderPrint(currentNode.leftChild);
preOrderPrint(currentNode.rightChild);
}

}
int findMin(Node rootNode)
{
// So keep traversing (in order) towards left till you reach leaf node,
//and then return leaf node's value
if (rootNode == null)
return -1;
else if (rootNode.leftChild == null)
return rootNode.value;
else
return findMin(rootNode.leftChild);
}
}
}

Time Complexity: $O(n)$

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.

Solution and Explanation

main.cs
Trie.cs
using System;

namespace chapter_7
{
class TrieNode
{
const int ALPHABET_SIZE = 26;

public TrieNode[] children = new TrieNode[ALPHABET_SIZE];
public bool isEndWord;

public TrieNode()
{
this.isEndWord = false;
for (int i = 0; i < ALPHABET_SIZE; i++)
{
this.children[i] = null; ;
}
}
//Function to unMark the currentNode as Leaf
public void markAsLeaf()
{
this.isEndWord = true;
}
//Function to unMark the currentNode as Leaf
public void unMarkAsLeaf()
{
this.isEndWord = false;
}

}
class Trie
{
TrieNode root;

public Trie()
{
root = new TrieNode();
}
//Function to get the index of a character 't'
public int getIndex(char t)
{
return t - 'a';
}
//Function to insert a key,value pair in the Trie
public void insertNode(string key)
{
//Empty string is not allowed
if (key == string.Empty)
return;

//using transform() function and ::tolower in STL to convert 'key' to lowercase
//transform(key.begin(), key.end(), key.begin(), ::tolower);
key = key.ToLower();
TrieNode currentNode = root;
int index = 0;

//Iterate the trie with the given character index,
//If the index points to NULL
//simply create a TrieNode and go down a level
for (int level = 0; level < key.Length; level++)
{
index = getIndex(key[level]);

if (currentNode.children[index] == null)
{
currentNode.children[index] = new TrieNode();
Console.WriteLine( key[level] + " inserted" );
}
currentNode = currentNode.children[index];
}

//Mark the end character as leaf node
currentNode.markAsLeaf();
Console.WriteLine( "'" + key + "' inserted" );
}
//Function to search given key in Trie
public bool searchNode(string key)
{
return false;
}
//Function to delete given key from Trie
public bool deleteNode(string key)
{
return false;
}
}
}


Time Complexity: $O(n)$

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.

Solution and Explanation

main.cs
Trie.cs
using System;

namespace chapter_7
{
class TrieNode
{
const int ALPHABET_SIZE = 26;

public TrieNode[] children = new TrieNode[ALPHABET_SIZE];
public bool isEndWord;

public TrieNode()
{
this.isEndWord = false;
for (int i = 0; i < ALPHABET_SIZE; i++)
{
this.children[i] = null; ;
}
}
//Function to unMark the currentNode as Leaf
public void markAsLeaf()
{
this.isEndWord = true;
}
//Function to unMark the currentNode as Leaf
public void unMarkAsLeaf()
{
this.isEndWord = false;
}

}
class Trie
{
const int ALPHABET_SIZE = 26;
TrieNode root;

public Trie()
{
root = new TrieNode();
}
public TrieNode getRoot()
{
return root;
}
//Function to get the index of a character 't'
public int getIndex(char t)
{
return t - 'a';
}
//Function to insert a key,value pair in the Trie
public void insertNode(string key)
{
//Empty string is not allowed
if (key == string.Empty)
return;

//using transform() function and ::tolower in STL to convert 'key' to lowercase
//transform(key.begin(), key.end(), key.begin(), ::tolower);
key = key.ToLower();
TrieNode currentNode = root;
int index = 0;

//Iterate the trie with the given character index,
//If the index points to NULL
//simply create a TrieNode and go down a level
for (int level = 0; level < key.Length; level++)
{
index = getIndex(key[level]);

if (currentNode.children[index] == null)
{
currentNode.children[index] = new TrieNode();
Console.WriteLine( key[level] + " inserted" );
}
currentNode = currentNode.children[index];
}

//Mark the end character as leaf node
currentNode.markAsLeaf();
Console.WriteLine( "'" + key + "' inserted" );
}
//Function to search given key in Trie
public bool searchNode(string key)
{
if (key == string.Empty)
return false;

key = key.ToLower();
TrieNode currentNode = root;
int index = 0;

//Iterate the Trie with given character index,
//If it is NULL at any point then we stop and return false
//We will return true only if we reach leafNode and have traversed the
//Trie based on the length of the key
for (int level = 0; level < key.Length; level++)
{
index = getIndex(key[level]);

if (currentNode.children[index] == null)
return false;
currentNode = currentNode.children[index];
}
if ((currentNode != null) & (currentNode.isEndWord))
{
return true;
}

return false;
}
//Helper Function to return true if currentNode does not have any children
public bool hasNoChildren(TrieNode currentNode)
{
for (int i = 0; i < ALPHABET_SIZE; i++)
{
if ((currentNode.children[i]) != null)
return false;
}
return true;
}
//Recursive function to delete given key
public bool deleteHelper(string key, TrieNode currentNode, int length, int level)
{
bool deletedSelf = false;

if (currentNode == null)
{
Console.WriteLine("Key does not exist");
return deletedSelf;
}

//Base Case: If we have reached at the node which points to the alphabet at the end of the key.
if (level == length)
{
//If there are no nodes ahead of this node in this path
//Then we can delete this node
if (hasNoChildren(currentNode))
{

currentNode = null; //clear the pointer by pointing it to NULL
deletedSelf = true;
}
//If there are nodes ahead of currentNode in this path
//Then we cannot delete currentNode. We simply unmark this as leaf
else
{
currentNode.unMarkAsLeaf();
deletedSelf = false;
}
}
else
{
TrieNode childNode = currentNode.children[getIndex(key[level])];
bool childDeleted = deleteHelper(key, childNode, length, level + 1);
if (childDeleted)
{
//Making children pointer also null: since child is deleted
currentNode.children[getIndex(key[level])] = null;
//If currentNode is leaf node that means currntNode is part of another key
//and hence we can not delete this node and it's parent path nodes
if (currentNode.isEndWord)
{
deletedSelf = false;
}
//If childNode is deleted but if currentNode has more children then currentNode must be part of another key.
//So, we cannot delete currenNode
else if (!hasNoChildren(currentNode))
{
deletedSelf = false;
}
//Else we can delete currentNode
else
{
currentNode = null;
deletedSelf = true;
}
}
else
{
deletedSelf = false;
}
}
return deletedSelf;
}

//Function to delete given key from Trie
public void deleteNode(string key)
{
if ((root == null) || (key == string.Empty))
{
Console.WriteLine("Null key or Empty trie error");
return;
}
deleteHelper(key, root, key.Length, 0);
}
}
}

Time Complexity: $O(n)$

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.

## C# Heaps and Hashing

### 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.

Solution and Explanation

main.cs
MaxHeap.cs
using System;
using System.Collections.Generic;

namespace chapter_8
{
class MaxHeap<T> where T: IComparable<T>
{

void percolateUp(int i)
{
if (i <= 0)
return;
else if (h[parent(i)].CompareTo ( h[i]) < 0)
{
// Swaps the value of two variables
T temp = h[i];
h[i] = h[parent(i)];
h[parent(i)] = temp;
percolateUp(parent(i));
}
}
public void maxHeapify(int i)
{
int lc = lchild(i);
int rc = rchild(i);
int imax = i;

if (lc < size() && (h[lc].CompareTo(h[imax]) > 0))
imax = lc;
if (rc < size() && (h[rc].CompareTo(h[imax]) > 0))
imax = rc;
if (i != imax)
{
T temp = h[i];
h[i] = h[imax];
h[imax] = temp;
maxHeapify(imax);
}
}

List<T> h = null;
public MaxHeap() {
h = new List<T>();
}
public int size() {
return h.Count;
}
public T getMax()
{
if (size() <= 0)
{
return (T)Convert.ChangeType(-1, typeof(T));
}
else
return h;
}
public void insert(T  key)
{
// Push elements into vector from the back
// Store index of last value of vector in  variable i
int i = size() - 1;
// Restore heap property
percolateUp(i);
}
public void printHeap()
{
for (int i = 0; i <= size() - 1; i++)
{
Console.Write( h[i] + " ") ;
}
Console.WriteLine("");
}
public void buildHeap(T [] arr, int size)
{
// Copy elements of array into the List h
for (int i = (size - 1) / 2; i >= 0; i--)
{
maxHeapify(i);
}
}
public int parent(int i)
{
return (i - 1) / 2;
}
public int lchild(int i)
{
return i * 2 + 1;
}
public int rchild(int i)
{
return i * 2 + 2;
}
public void removeMax()
{
if (size() == 1)
{
// Remove the last item from the list
h.RemoveAt(h.Count - 1);
}
else if (size() > 1)
{
// Swaps the value of two variables
T temp = h;
h = h[size() - 1];
h[size() - 1] = temp;
// Deletes the last element
h.RemoveAt(h.Count - 1);
// Restore heap property
maxHeapify(0);
}

}

}
}

Time Complexity: $O(n)$

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:

Solution and Explanation

main.cs
MinHeap.cs
using System;
using System.Collections.Generic;

namespace chapter_8
{
class MinHeap<T> where T : IComparable<T>
{
List<T> h = null;
public int parent(int i)
{
return (i - 1) / 2;
}
public int lchild(int i)
{
return i * 2 + 1;
}
public int rchild(int i)
{
return i * 2 + 2;
}

void minHeapify(int i)
{
int lc = lchild(i);
int rc = rchild(i);
int imin = i;
if (lc < size() && (h[lc].CompareTo(h[imin]) < 0))
imin = lc;
if (rc < size() && (h[rc].CompareTo(h[imin]) < 0))
imin = rc;
if (i != imin)
{
T temp = h[i];
h[i] = h[imin];
h[imin] = temp;
minHeapify(imin);
}
}

//percolateUp(): It is meant to restore the
//heap property going up from a node to the root.
void percolateUp(int i)
{
if (i <= 0)
return;
else if (h[parent(i)].CompareTo(h[i]) > 0)
{
// Swaps the value of two variables
T temp = h[i];
h[i] = h[parent(i)];
h[parent(i)] = temp;
percolateUp(parent(i));
}
}

public MinHeap()
{
h = new List<T>();
}

public int size()
{
return h.Count;
}

public T getMin()
{
if (size() <= 0)
{
return (T)Convert.ChangeType(-1, typeof(T));
}
else
{
return h;
}
}
public void insert(T key)
{
// Push elements into vector from the back
// Store index of last value of vector in  variable i
int i = size() - 1;
// Restore heap property
percolateUp(i);
}
public void removeMin()
{
if (size() == 1)
{
// Remove the last item from the list
h.RemoveAt(h.Count - 1);
}
else if (size() > 1)
{
// Swaps the value of two variables
T temp = h;
h = h[size() - 1];
h[size() - 1] = temp;
// Deletes the last element
h.RemoveAt(h.Count - 1);
// Restore heap property
minHeapify(0);
}

}
public void buildHeap(T[] arr, int size)
{
// Copy elements of array into the List h
for (int i = (size - 1) / 2; i >= 0; i--)
{
minHeapify(i);
}
}

//Bonus function: printHeap()
public void printHeap()
{
for (int i = 0; i <= size() - 1; i++)
{
Console.Write( h[i] + " ");
}
Console.WriteLine("");

}
}
}

Time Complexity: $O(n + klogn)$

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.

Solution and Explanation

using System;
using System.Collections.Generic;

namespace chapter_9
{
class Program
{
static bool isSubset(int [] arr1, int [] arr2, int size1, int size2)
{
if (size2 > size1)
{
return false;
}
HashSet<int> ht = new HashSet<int>();
// ht stores all the values of arr1
for (int i = 0; i < size1; i++)
{
// following the last element of the container
// If key is not present in the unordered_set then insert it
if (!ht.Contains(arr1[i]))
}

// loop to check if all elements of arr2 are also in arr1
for (int i = 0; i < size2; i++)
{
// If found it will return iterator to that key
if (!ht.Contains(arr2[i]))
return false;
}
return true;
}
static void Main(string[] args)
{
int []arr1 = { 9, 4, 7, 1, -2, 6, 5 };
int []arr2 = { 7, 1, -2 };

Console.WriteLine(isSubset(arr1, arr2, 7, 3));
return;
}
}
}

Time Complexity: $O(m+n)$ 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:

$a+b = c+d$

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

Solution and Explanation

using System;
using System.Collections.Generic;

namespace chapter_9
{
class challenge_5
{
static string findPair(int[] arr, int size)
{

string result = "";

// Create HashMap with Key being sum and value being a pair i.e key = 3 , value = {1,2}
// Traverse all possible pairs in given arr and store sums in map
// If sum already exist then print out the two pairs.

Dictionary<int, int[]> hMap = new Dictionary<int, int[]>();
int sum;
int[] prev_pair = null;
for (int i = 0; i < size; ++i)
{
for (int j = i + 1; j < size; ++j)
{
sum = arr[i] + arr[j]; //calculate sum

if (!hMap.ContainsKey(sum))
{
// If the sum is not present in Map then insert it along with pair
int[] temp_Arr = new int;
temp_Arr = arr[i];
temp_Arr = arr[j];
hMap[sum] = temp_Arr;

}
else
{
prev_pair = hMap[sum];
// Since array elements are distinct, we don't
// need to check if any element is common among pairs

result += "{" + prev_pair.ToString() + "," + prev_pair.ToString() + "}{" + arr[i].ToString() + "," + arr[j].ToString() + "}";
return result;

}
}
}//end of for
return result;
}
static void Main(string[] args)
{
int[] arr = { 3, 4, 7, 1, 12, 9 };
Console.WriteLine(findPair(arr, 6));
}
}
}

Time Complexity: $O(n^2)$

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

1. Reverse a string in C#
2. Check if a given string is a palindrome
3. Rotate an array
4. Find the second largest integer within an array using one loop
5. Convert a 2D Array to a 1D Array
6. Explain and implement the MergeSort algorithm
7. Find out if a linked list is circular
8. Balance a binary search tree
9. Search a sorted array with lowest time complexity possible
10. 0-1 Knapsack problem
1. Match beginning and ending parenthesis in a string
2. Shuffle an array of integers in place
3. Find the ancestors of a given node in a BST
4. Find the shortest path between two vertices in a graph
5. Count the number of edges in an undirected graph
6. Check balanced parenthesis using a stack
7. Sort values in a stack
8. Reverse first k elements in a queue
9. Find the middle node of a linked list

## What to learn next

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.

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Happy learning! WRITTEN BYRyan Thelin

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