Programming Techniques Guide

Welcome to the comprehensive guide to programming techniques and algorithms! This documentation covers essential techniques used in competitive programming, software development, and algorithmic problem-solving.

Categories & techniques

Our techniques are organized into the following categories with their respective techniques:

Category	Description	Techniques
🔍 Brute Force & Search	Techniques for systematically exploring solution spaces and finding optimal solutions through exhaustive search methods.	Boolean Counter • Generating Subsets • Recursive Backtracking • Search Pruning • Meet-in-the-Middle • Permutation Enumeration
📊 Counting & Precomputation	Methods for efficiently counting elements, managing frequencies, and preprocessing data for faster queries.	Frequency Arrays • Static Array Queries • Prefix Arrays • Difference Arrays • Sieve of Eratosthenes
🎯 Dynamic Programming	Advanced techniques for solving complex problems by breaking them down into simpler subproblems.	Top-Down & Bottom-Up • Coin Change • Knapsack • Longest Increasing Subsequence • Grid Path DP • Edit Distance • Counting Tilings • Bitmask DP • DP on Trees / Graphs
🌐 Graph & Network Modeling	Algorithms and techniques for working with graphs, networks, and relational data structures.	Graph Basics • DFS / BFS • Dijkstra / Bellman-Ford • Floyd–Warshall • Union-Find • Minimum Spanning Tree • Tree Algorithms • LCA & Tree Queries • Strong Connectivity & 2SAT • Eulerian & Hamiltonian • Flows & Matchings
📐 Geometry & Spatial Modeling	Mathematical approaches for solving geometric and spatial problems efficiently.	Points & Lines • Distance Functions • Polygon Area • Complex Numbers • Closest Pair • Sweep Line • Convex Hull
🔤 String & Bitwise Techniques	Specialized algorithms for string manipulation and bitwise operations.	KMP / Z Algorithm • Trie / Aho-Corasick • String Hashing • Bit Representation & Sets • Bitmask Tricks
🎮 Simulation & Modeling	Techniques for simulating real-world scenarios and modeling complex systems.	Two Pointer / Sliding Window • Nearest Smaller Elements • Sliding Window Minimum • Binary Search on Answer • Greedy Algorithms
🏗️ Data Structures	Essential data structures and their applications in algorithm design.	Dynamic Arrays • Sets & Maps • Iterators & Ranges • Segment Tree / BIT • Lazy Segment Tree • 2D Segment Tree / BIT • Heap / Priority Queue • Disjoint Set (DSU) • Sqrt Decomposition • Mo’s Algorithm
📐 Mathematical Formulas	Essential mathematical formulas and concepts for geometric, counting, trigonometric, and algebraic problems.	Geometric Formulas • Combinatorics & Counting • Binomial & Catalan • Inclusion–Exclusion • Number Theory • Primes & Factors • Modular Arithmetic • Trigonometry • Linear Algebra • Linear Recurrences & Matrices • Probability & Randomized • Combinatorial Games

Getting started

Each category contains:

• Overview: Introduction to the category and its techniques
• Individual technique pages: Detailed explanations with examples and use cases

Navigate through the categories using the sidebar or the tabs above to explore specific techniques.

Contributing

This documentation is designed to be a living resource. Feel free to contribute improvements, examples, or additional techniques!