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What is Competitive Programming?

Competitive programming is a technique that makes you a master in coding. Competitive programming provides some advantages. These advantages are as follows:

  • It helps us in getting a job.
  • It also improves our logical analysis skills.
  • It also enhances our creativity.

In this article, we will see the important topics of competitive programming to enter into the competitive programming field.

Definition of Competitive Programming

Competitive programming is an art or activity that requires creativity in our thinking power that helps us to tackle complex coding problem. It is an event that usually organises over the internet where the participant is called a sport programmer. There is a host machine that judges the entire event. The work of the sports programmers is to write code that solves a given mathematical or logical problem. These events were first held in the 1970s. The interest in this event increases rapidly every year. Facebook, Google, and ACM ICPC are some companies that organise these types of events. 

  • Well-define problems: There are a few problems given in competitive programming. These problems have constraints of variables, assumptions, and other limitations. 
  • Computer programs: We have to write the source for the given problems. These programs are command line programs and are not for the web applications.
  • Specified limits: There is some limited time given to us in which we have to write the code and then compile the code, to pass all the test cases. 

The main focus of these competitive programs is to check the participant's algorithm knowledge, logical reasons, data structure and other skills. This competitive programming is very difficult because it has a limited time period to solve the problems. JAVA and C++ are the most common programming language that is used in competitive programming because these programming languages have run time efficiency in comparison to any other programming language. 

Advantages of Competitive Programming

There are so many benefits to competitive programming. These are as follows:

1. Getting Hired

The participant who participates in competitive programming helps participant to become a desirable candidate for companies. The participants in competitive programming have a chance to get a job offer from companies like Apple, Facebook, IBM, Google, and more. Some tech companies organise these events to check the capacity of their employees. If someone does well in these competitive programming, that is an indicator of their technical talent and abilities. Some companies also sponsor competitive programming.

2. Teamwork Skills

To participate in this event, a team is allowed to enter in this event. We have to communicate with our teammates in high-pressure situations. This is a very good skill. When we work as software engineers then, we have to share with our other colleagues. Excellent communication for the team leader makes a desirable candidate. The main idea of Companies is to know whether you can work effectively with your teammates or not.

3. Interview Preparation

If someone is trying to get a job in a software company, then companies will test their knowledge of data structures and algorithms. Then the participant has good knowledge and an advanced understanding of these concepts. The coding interview and competitive programming are the same. In both environments, the participant worked under high-pressure conditions. When many other candidates may not be able to adjust to this environment, your competition experience gives you the experience. 

 4. Make us faster and more focused

After participating in competitive programming, we become more disciplined, faster, and more efficient. This gives us an experience of how to focus on a task and execute it efficiently. 

How does competitive programming work?

Prerequisites for competitive programming

To enter into competitive programming, we must have knowledge of programming language and basic data structures. The most used programming language in competitive programming is C++. It is prevalent due to its speed. 

Data Structures and Algorithms

We have to know the fundamentals of data structures and algorithms. Understanding data structures and algorithms are the main part of competitive programming. 

Google Code Jam, Google Hash Code, and Google Kickstart are some events that are hosted by Google.

In a competitive programming event, the primary question comes mathematical or logical in nature, typically involving one from string analysis, number theory, combinatorics, graph theory, geometry, and data structures. It has two steps. These steps are as follows.

  1. The first step is the construction of an algorithm.
  2. The second step is implementing the algorithm in a programming language.

These events are automatically judged by the host machine. The output of the source code will check in the test case method. When someone first clears the test case, then more rank will be given to them by the host machine.

Topics in Competitive Programming

  1. Data structure.
  2. C++
  3. Number theory.
  4. Arithmetic paradigms.
  5. Graph algorithm.

1. Data Structure

A data structure is also a container for all the data types. The understanding of data structure is very important for competitive programming. You can take the help of data structure to decide the competitive programming. If you learned the following things, then you are a master in the data structure. These are as follows.

  • Stacks
  • Queues
  • Linked List
  • Binary Tree
  • Binary Search Tree
  • Graphs
  • Tries
  • Hash tables
  • Heap

2. C++

C++ is the popular programming language for competitive programming. It has a library which is known as STL (Standard Template Library). STL (Standard Template Library) is a collection of C++ template classes which provides data structures and functions. C++ follows the concept of other programming language like Java and Object Oriented Programming language. Java provides library facilities which are also known as collections. But java is slower in comparison to C++. There is another language for competitive programming. This language is python. Because it is user-friendly in nature and the length of the code is short. But python is very slow in comparison with C++.

3. Number Theory

There is a lot of question that comes from math. So it is essential to know basic mathematics. Below are some topics that are important for competitive programming. The basic fundamental of the below topics can help you to succeed in competitive programming.

4. Arithmetic Paradigms

Algebra

  • All the positive natural integer starts from 1, i.e 1,2,3,4,5,6,7,8,9,10..........
  • Sum of first n integer = n(n+1)/2.
  • Factorial of a number is denoted by n! i.e. n!=1*2*3...*n.

Arithmetic Sequence

The series of the number such that the difference between each number is constant is known as an Arithmetic sequence. 

Sum of an arithmetic sequence with n terms is =n[2a+d(n-1)]/2

Where n = number of terms.

 a = first term.

 d = common difference

Geometric Sequence

The series of the number such that the next term is obtained by multiplying the constant number is known as a geometric sequence. For example, 2, 6, 18, 54. The common multiplier is 3.

Algorithmic paradigms

There is a technique to solve the process known as Arithmetic paradigms. There are four types of Arithmetic paradigms. These are divide & conquer, greedy algorithms, brute force, and dynamic programming.

Brute force is the algorithm that solves the problem by trial and error method. Linear search is an example of a Brute force algorithm. With the help of Linear search, we can find a target value by going through every single value in a list.

Dynamic programming is also an algorithm that solves the problem by breaking it into subparts. 

5. Graph Algorithm

A graph is a non-linear data structure. It consists of nodes and edges. 

Below are some concepts of the graph that we should learn to crack competitive programming.

These are as follows.

  • Depth First Search (DFS)
  • The shortest path from every vertex to every other vertex (Floyd Warshall)
  • Breadth First Search (BFS)
  • The shortest route from source to all vertices (Dijkstra)

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