Algorithms & Data Structures
Welcome to the comprehensive algorithms and data structures section! This collection contains implementations, explanations, and practice problems for various algorithmic techniques commonly encountered in software engineering interviews.
Algorithm Categories
Core Techniques
- Backtracking - Systematic exploration of solution spaces
- Binary Search - Efficient searching in sorted arrays
- Dynamic Programming - Optimization through memoization
- Greedy - Local optimization strategies
Data Structures
- Binary Tree Traversal - Tree navigation techniques
- Heap - Priority queue implementations
- Graphs and Matrices - Graph algorithms and matrix operations
Problem-Solving Patterns
- Sliding Window - Efficient array/string processing
- Multi Pointers - Two-pointer and multi-pointer techniques
- Merge Interval - Interval manipulation problems
- Next Greater Element - Stack-based solutions
- Prefix Sum - Cumulative sum techniques
Specialized Topics
- Strings - String manipulation algorithms
- Sortings - Various sorting algorithms
- Search - Advanced search techniques
- Implementation - Complex implementation problems
- Constructive Algo - Constructive algorithms
Utilities
- Utils - Helper functions and common utilities
How to Use This Section
Each algorithm category contains:
- index.md - Overview and explanation of the technique
- TECHNIQUE.md - Detailed technique breakdown (where applicable)
- TEMPLATE.md - Code templates and patterns (where applicable)
- Problem implementations - Actual coding solutions with explanations
Interview Preparation Tips
- Start with fundamentals - Master basic data structures first
- Practice patterns - Focus on recognizing problem patterns
- Time complexity - Always analyze and optimize your solutions
- Edge cases - Consider boundary conditions and special cases
- Code clarity - Write clean, readable, and well-commented code
Difficulty Levels
Problems are generally organized by technique rather than difficulty, but you can expect:
- Beginner: Basic implementations and simple problems
- Intermediate: Standard interview questions with multiple approaches
- Advanced: Complex problems requiring deep algorithmic knowledge
Happy coding! 🚀