Competitive Programming – A Complete Guide
Last Updated :
04 Apr, 2024
Competitive Programming is a mental sport that enables you to code a given problem under provided constraints. The purpose of this article is to guide every individual possessing a desire to excel in this sport. This article provides a detailed syllabus for Competitive Programming designed by industry experts to boost the preparation of the readers.
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What is Competitive Programming?
Competitive programming is a mind sport, where people compete against each other to solve some programming questions/logic with an efficient approach and within a time constraint. The goal of competitive programming is to write code to solve a problem within a given timeframe.Â
Competitive programming is the best way to master your analytical thinking, and logical thinking and improve your coding skills. It is now being considered by many tech giants like Google and Facebook. Also, Facebook organizes the Meta Hacker Cup annually to promote all the Competitive Programmers around the world to compete against one another and earn a chance to get hired at Meta.
Here are some reasons about why you should start Competitive Programming:
- Mental Agility and Quick Thinking: By practicing competitive programming, you start thinking quickly and within the given timeframe and this improves your mental agility and helps enhance your thinking ability.
- Competitive Spirit: Competitive programming can be fun for those who enjoy the thrill of competition. Solving challenging problems that too within a timeframe boosts confidence and a sense of accomplishment.
- Career Prospect: Competitive programming is very important when it comes to technical interviews for software engineering-related jobs. Many tech giants use competitive programming contests as a medium of recruitment. Companies like Google, ServiceNow, Atlassian, etc. have technical interviews based on competitive programming problems.
- Learning Opportunity: In Competitive programming, we get a wide range of variety of problems and various arithmetic concepts. Competitive programming exposes various data structures and algorithms which help us better understand the complexity of problems.
- Personal Growth as a Programmer: Competitive programming is one of the best ways to grow as a programmer. It helps you get a command over problem-solving, as you’ve to solve challenging problems within a time limit.Â
- Networking: Participating in various coding contests gives you a chance to be a part of communities with like-minded people. Here in these communities, you get various important resources and guidance from experts who can help you get so many opportunities like referrals, job-opening information, mentorship, etc.Â
Basics of Competitive Programming:
- What is Competitive Programming and How to Prepare for It?
- Competitive Programming (CP) Handbook with Complete Roadmap
- Fast I/O: CPP, Java, Python
- Useful libraries: CPP, Java, Python
- Input/Output Files: Set 1, Set 2
- Tips and Tricks: Set 1, Set 2
- Input Methods: CPP, Java, Python
- Template: CPP
- Language: CPP, Java, Python
- Time Complexity: AnalysisÂ
- Setting up Competitive Programming Environment: Sublime: CPP, Visual Studio: CPP and Python
- CSES Problem Set
Basics Of Array , String, Greedy and Bit Manipulation
- Reverse an array(Related Problems: Problem 1, Problem 2)
- Sum of Digits
- Program to Check if a Given String is Palindrome in C, Python (Related Problem)
- Sum of array elements(Related Problem)
- Maximum and Minimum element of array(Related Problem)
- Counting frequencies of array elements(Related Problems: Problem 1, Problem 2)
- Float and Precision: CPP, Java, Python
- Prefix sum, 2D Prefix Sum, Difference Array | Range update query in O(1): (Related Problems: Problem 1, Problem 2)
- Coordinate Compression: (Related Problem)
- Kadane Algorithm: (Related Problem)
- Activity Selection Problem: (Related Problem)
- Job Sequencing Problem: (Related Problem)
- Sliding Window: (Related Problem)
- Logical Operators: CPP Set 1, Set 2, Java, Python
- Bit Manipulation: Set 1, Set 2, Set 3(Related Problems: Problem 1, Problem 2, Problem 3)
- Bitset CPP
- Top 50 Array Coding Problems for Interviews
- Top 50 String Coding Problems for Interviews
Number Theory and Combinatorics
- Prime Number(Related Problem)
- Sieve of Eratosthenes(Related Problem)
- Segmented Sieve (Related Problem)
- Find all divisors of a natural number (Related Problem)
- Least prime factor of numbers upto N (Related Problem)
- All prime factors of a number(Related Problem)
- Prime Factorization using Sieve O(log n) for multiple queries
- Sum of all factors of a number(Related Problem)
- Gcd of Two numbers, Lcm of two numbers(Related Problem)
- Linear Diophantine Equations
- Euclidean algorithms (Basic and Extended)
- Euler’s Totient Function(Related Problem)
- Euler’s Totient function for all numbers smaller than or equal to n
- Inclusion Exclusion PrincipleÂ
- Pigeon Hole Principle
- Modular Operations
- Modular Inverse: (Related Problem 1, Problem 2)
- Chinese Remainder Theorem: Set 1, Set 2
- Power(x, y) in O( logN )
- Power(x, y) % mod: (Related Problem 1, Problem 2)
- Matrix Exponentiation: (Related Problem)
- Permutation and Combination: Set 1, Set 2, Quiz 1, Quiz 2
- nCr: Set 1, Set 2
- nCr % mod: Set1, Set 2: (Related Problem)
- nCr % mod for multiple queries: (Related Problem)
- Catalan numbers: Applications and Related Problem
- Gaussian Elimination
Searching, Sorting and Basic Data Structures
- Linear Search(Related Problems: Problem 1, Problem 2)
- Binary Search, Unbounded Binary Search(Related Problems :Â Problem 1, Problem 2, Problem 3)
- Inbuilt sorting O(logN): CPP, Java, Python(Related Problems: Problem 1, Problem 2, Problem 3, Problem 4)
- Merge Sort(Related Problems: Problem 1, Problem 2)
- Quick Sort(Related Problems: Problem)
- Stack: Implementation in CPP, Java, Python(Related Problems: Problem 1, Problem 2, Problem 3)
- Queue: Implementation in CPP, Java, Python(Related Problems: Problem 1, Problem 2 , Problem 3)
- Deque: Implementation in CPP, Java, Python(Related Problems: Problem)
- Priority Queue: Implementation in CPP, Java, Python(Related Problems: Problem 1, Problem 2, Problem 3)
Tree and Graphs
- Tree BFS, Tree DFS (Related Problems: Problem 1, Problem 2, Problem 3)
- Graph BFS, Graph BFS 2, Graph DFS (Related Problems: Problem 1, Problem 2)
- Dijkstra’s Shortest Path Algorithm(Related Problems: Problem 1, Problem 2)
- Bellman – Ford Algorithm(Related Problem)
- Floyd Warshall Algorithm(Related Problem)
- 0-1 BFS, Dial’s Algorithm
- Detect cycle: Directed, Undirected(Related Problems: Problem 1, Problem 2)
- Disjoint set(union-find): Set 1, Set 2, Set 3(Related Problem)
- Topological Sorting, Kahn’s Algorithm(Related Problem)
- Minimum Spanning Tree: Prim’s Algorithm, Kruskal Algorithm(Related Problem)
- Bipartite or not, M-Coloring(Related Problems: Problem 1, Problem 2, Problem 3)
- Strongly Connected Components: Tarjan, Kosaraju(Related Problems: Problem 1, Problem 2)
- Euler Path: Undirected, Directed(Related Problem)
- Flow Algorithms: Set 1, Set 2, Dinic’s Algorithm(Related Problems: Problem 1, Problem 2)
- Diameter of Tree
- Centroid Decomposition
- Lowest Common Ancestor
- Top 50 Tree Coding Problems for Interviews
Recursion and Dynamic Programming
- Recursion: Â Quiz 1, Quiz 2, Quiz 3, Quiz 4, Quiz 5, Quiz 6, Quiz 7 (Related Problems: Problem 1, Problem 2, Problem 3)
- Backtracking: (Related Problems: Problem 1, Problem 2)
- Dp Introduction: Set 1, Set 2, Set 3, Set 4, Set 5
- Most useful Dynamic Programming questions
- Additional DP Problems : Problem 1, Problem 2, Problem 3, Problem 4
- Dp on Trees: Set 1, Set 2
- Dp on Bit Masking: Set 1, Set 2, Set 3
- Digit Dp
- Top 50 Dynamic Programming Coding Problems for Interviews
String Algorithms
Geometry and Game Theory
Advance Data Structures
- Trie: Set 1, Set 2, Set 3, (Related Problems: Problem 1, Problem 2, Problem 3, Problem 4, Problem 5)
- Fenwick Tree: Set 1, Set 2, Set 3, Set 4, (Related Problem)
- Segment Tree: Set 1, Set 2, Set 3 (Related Problem)
- Sparse Table: Set 1, Set 2
- Sqrt Decomposition: Set 1, Set 2
- Heavy Light Decomposition: Set 1, Set 2
- Meet in the Middle
- MO’s Algorithm, Problem
- Policy based Data Structure
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