Data Structure & Algorithm

-


I am going to start the complete data structure and algorithm blog series to help the developer community understand the basics and help them become more productive in their work environment. As we all are under lockdown until the next update from the government, I have decided to support my friends and colleague to understand the data structure and algorithm. Let's begin by separating the data structure and algorithm in two terms.
When you hear about data structure, what comes first to your mind. I believe most of you thought of storing any form of data in an efficient way. Yes, You are correct 👍.
Now, Second and the most important term is an algorithm, It is a set of rules to be followed to solve a problem.
To gain more understanding of the data structure and algorithm, let us take an example:-
E.g., We are all going to attend the google conference and they have a single registration desk. If we all reach the registration counter together, to register ourselves. Such a situation could get out of hand for the crew member to handle So, What do you think? What are the respective steps that need to be taken care of by the organizing committee to avoid such a situation?
I hope, everyone is on the same page. There should be a queue system on a first come first serve basis. We analyze the problem and come up with the solution that there must be a queue data structure where each participant will be placed in an organized manner. Now, You have a good understanding of data structure, why do we need it?

                                    iOS Concurrency：Getting NSOperation and Dispatch Queues ...
Let's understand the advantages of data structure in the above example.
  1. Unorganized registration to the organized registration desk.
  2. Processing will be an efficient time.
We will look into the topics further delving into data structure for a deep dive into this specialization.
Location: Delhi, India

Comments

  1. UnknownMay 30, 2020 at 8:24 AM

    Good job keep it up. Please start a series with each type of recursion with detailing like when to use when not.

    ReplyDelete

Post a Comment

Popular posts from this blog

Recursion

-
Image
The process in which a function calls itself and only works where we call the same operation multiple times with different inputs. In every call, we try to make the problem smaller. There must be a base case where the system will stop the recursion and give you a result back. It internally stores the recursion state in the method call stack. If there is no base condition in the recursion method then it will go into an infinite loop and you might face the StackOverflow Exception . There are several types of recursion:- Head Recursion Tail Recursion Tree Recursion Nested Recursion Head Recursion It will call recursively first then at the end do all the computation. private static int factorial( int number) { return (number== 1 )? number : number* factorial (number- 1 ) ; } factorial(5) (5* factorial(5-1)) (5* (4* factorial(4-1)) (5* (4* (3*factorial(3-1))) (5* (4* (3* (2*factorial(2-1)))) (5* (4* (3* (2* (1*1))))) output = 120 Tail Recur...
Read more

Stack

-
Image
The Stack  looks more like a container which holds the element, will insert element from the top and remove from the top only. It follows the Last in First out(LIFO)  or First In Last out (FILO)  approach. Java uses the method stack area to hold the state of the method if some method calls another method inside it.   public class Demo { public static void main(String[] args) { new Demo().firstCall(); System. out .println( "Main" ); } public void firstCall() { secondCall(); System. out .println( "First" ); } private void secondCall() { thirdCall(); System. out .println( "Second" ); } private void thirdCall() { System. out .println( "Third" ); } } This is how it maintains the method call in the method stack area. It will remove from the top every time and complete its method execution and remove next's top from the stack. This process will continue until th...
Read more