Queue - Introduction

Queue (abstract data type) - Wikipedia
  • Follows First In First Out (FIFO)
  • Implementation Options of queue :
    • Arrays
      • Linear queue
      • Circular queue
    • Linked List
      • Linear queue (only, and not Circular queue)

Why we need circular queue ?
       
Because in the array implementation of linear queue, when we perform deque operation, it causes few blank cells in linear queue (at the start of queue). Due to this, we waste a lot of space.
Also, we do not want to shift the elements in the array to left (or start) so as to prevent empty cells at start as it will take O(n) time. We have to do it in O(1) time. For doing that we can again add new elements to the start and at the same time maintaining two pointers i.e. startOfQueue and endOfQueue. (See actual code implementation of circular queue using arrays)


When to use queue / Advantages of queue ?

 1. When we want to access data in FIFO order.
2. Data is not easily corrupted as the insertion and deletion of the elements in queue is done in a particular fashion.

When to avoid queue / Disadvantages of Queue ?

 Random access is not possible. If we have done a mistake while enqueueing, it is very difficult to rectify it.


Comments

Post a Comment

Popular posts from this blog

Binary Heap - Introduction

Image
#Image Credit - GeeksForGeeks Types of heap: Min Heap - every node is less than or equal to  its children(s) Max Heap - every node is more than or equal to its children(s) Operations on any heap : create insert extract/delete - we can extract/delete only the top node in any heap traverse delete entire heap get size of heap peek top of heap We should prefer implementing binary heap using arrays and not linked list, as during bottom to top heapify, in reaching the bottom rightmost node we take only 0(1) time in case of array but we take 0(n) time in case of linked list because first, we need to level order traverse the binary heap tree to get bottom-most rightmost element.  Heaps are used to efficiently implement:  Prim's Algorithm Heapsort Priority queue
Read more

Divide and Conquer - Introduction

Image
What is Divide and Conquer? Divide and Conquer is an algorithm paradigm in which we break down a given problem into smaller sub-problems of similar type until the sub-problems are small enough to be solved directly. The solution to these sub-problems are then combined to give a solution to the original problem.  Study the diagram below, it will then make more sense about what we do in Divide and Conquer : Where to Apply Divide and Conquer? The Divide and Conquer can be applied to all those problems that show Optimal Substructure property.  So, What is this Optimal Substructure property now? If we can break down a problem into similar sub-problems and the solution of these sub-problems can be used to create the solution of the whole problem, then that problem is said to have the Optimal Substructure property. For eg. : Fibonacci(n) = Fibonacci(n-1) + Fibonacci(n-2),    In this example, we can see that if we want to find the Fibonacci number at the nth place, we can br...
Read more

Bubble Sort

Time complexity - O(n^2)  || Space Complexity - O(1) Bubble sort is an inplace sorting algorithm, that means we do not any extra space while bubble sorting public class Main {     public static void main(String[] args) throws Exception {         int[] arr={1,4,4,5,6,2,3,90,120,43,0};                  System.out.println("UnSorted Array :");         for(int i=0;i<arr.length;i++){             System.out.print(arr[i]+" ");         }         System.out.println();         // bubble sort         for(int i=0;i<arr.length-1;i++){ // iterates through first to last cell             for(int j=0;j<arr.length-1-i;j++){ // inner loop controls swapping and extent to which swapping is to be performed in array     ...
Read more