A comprehensive, curated collection of 370+ LeetCode problem solutions featuring in-depth explanations, complexity analysis, and step-by-step implementation guides.
This repository serves as a structured learning resource for developers preparing for technical interviews or looking to strengthen their problem-solving skills. Each solution goes beyond basic code implementation to provide conceptual understanding and optimization techniques.
- 370+ Problems Solved - Extensive coverage across all difficulty levels and problem categories
- Deep Dive Analysis - Detailed explanations of approach, intuition, and thought process
- Complexity Breakdown - Time and space complexity analysis for each solution
- Step-by-Step Documentation - Clear, guided walkthroughs to understand implementation
- Multiple Approaches - Where applicable, multiple solution strategies are discussed
- Organized Structure - Easy navigation with descriptive file names
This library covers a wide range of algorithmic concepts including:
- Arrays & Strings - Two pointers, sliding window, prefix sums
- Dynamic Programming - Classic DP patterns and optimization
- Binary Search - Search space reduction and binary search variants
- Trees & Graphs - Traversals, DFS, BFS, shortest paths
- Backtracking - Combinatorial problems and constraint satisfaction
- System Design - Data structure design and implementation
- Database - SQL queries and optimization
- Mathematics - Number theory, geometry, and combinatorics
Each problem is contained in its own Markdown file with a descriptive name. Files follow the format:
Problem Title.md
Example files include:
Two Sum.mdBinary Search.mdLongest Substring Without Repeating Characters.md
- Browse by Problem Name - Use the file list to find specific problems
- Search by Topic - Use GitHub's search functionality to filter by algorithm type or pattern
- Sequential Learning - Start with easier problems and progress to more complex ones
- Interview Preparation - Review problems by company or difficulty level
Each solution document typically includes:
- Problem Statement - Clear description of the problem
- Approach & Intuition - Thought process and strategy
- Algorithm Steps - Detailed breakdown of the solution
- Implementation - Clean, well-commented code
- Complexity Analysis - Time and space complexity
- Edge Cases - Important test cases and considerations
- Variations - Alternative approaches or related problems
This is a personal learning repository. However, if you spot any errors or have suggestions for improvements, feel free to open an issue.
For additional practice and learning:
Created and maintained by Alex Alagoa Biobelemo
Note: Solutions are meant for learning purposes. Understanding the approach is more valuable than memorizing code. Happy coding! 🚀