🔍 Mastering Algorithms & Data Structures for Big Tech Interviews

This repository is dedicated to learning, implementing, and mastering core algorithms essential for cracking interviews at top tech firms.

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📌 Categories Covered

1. 📊 Sorting & Searching

• Quick Sort
• Merge Sort
• Heap Sort
• Binary Search (variations)
• Kth Smallest/Largest Element
• Search in Rotated Sorted Array

2. 🔁 Recursion & Backtracking

• Subset Generation
• Permutations
• N-Queens Problem
• Sudoku Solver
• Word Search
• Combination Sum

3. 💡 Greedy Algorithms

• Activity Selection
• Interval Problems (Merge/Overlap)
• Huffman Encoding
• Fractional Knapsack

4. 🧠 Dynamic Programming

• 0/1 Knapsack
• Longest Common Subsequence (LCS)
• Edit Distance
• Matrix DP (Unique Paths, Min Path Sum)
• DP on Trees
• Bitmask DP (Advanced)

5. 🌐 Graph Algorithms

• BFS & DFS (including cycle detection)
• Topological Sort
• Dijkstra’s Algorithm
• Bellman-Ford
• Floyd-Warshall
• Union-Find (Disjoint Set)
• MST (Prim’s & Kruskal’s)
• Strongly Connected Components (Kosaraju/Tarjan)

6. 🔲 Sliding Window & Two Pointers

• Longest Substring with K Distinct Characters
• Max Sum Subarray of Size K
• Trapping Rainwater

7. 📐 Binary Search on Answer

• Minimize the Maximum
• Painters Partition Problem
• Allocate Books
• Koko Eating Bananas

8. 🔡 Trie & String Algorithms

• Trie (Prefix Tree)
• KMP Algorithm
• Rabin-Karp
• Z-Algorithm

9. 🧮 Segment Tree & Fenwick Tree (BIT)

• Range Query & Updates
• Lazy Propagation

10. ⚙️ Bit Manipulation

• XOR Patterns
• Set/Unset Bits
• Power of 2
• Bitmask DP (Advanced)

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🚀 Goal

• 🧠 Deep understanding of each algorithm
• 🛠️ Clean and testable code (preferably in Java)
• ✅ Check off each topic as it’s completed

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📁 Structure

Each algorithm will be placed under its respective folder: