The final frontier. Phase 3 is where good problem-solvers become great ones — tackling Hard-level DSA problems that appear in FAANG interviews, competitive programming, and real-world system design.

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📋 Table of Contents

• Phase 3 Objective
• Topics Covered
• Progress Tracker
• Problem Log
• Key Learnings
• How to Use This Repo
• Full Challenge Journey
• Author

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🎯 Phase 3 Objective

Phase 3 is the most demanding leg of the 100 Days challenge. The focus shifts from understanding patterns to mastering them under pressure — optimizing for time, space, and elegance.

Goal	Description
🔥 Elite Problem Solving	Tackle problems that stump most candidates
⚙️ Advanced Optimization	Push beyond O(n log n) — think O(n), O(1) space
🧩 Complex Pattern Chains	Combine multiple DSA patterns in one solution
🏆 FAANG Readiness	Solve problems directly from top company interview banks
🧠 Competitive Programming	Build instincts for timed, high-pressure environments

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🧠 Topics Covered

Phase 3 — Hard DSA Topics
│
├── 🔗 Advanced Dynamic Programming (DP on Trees, Intervals, Bitmask)
├── 🌐 Graphs (Dijkstra, Bellman-Ford, Topological Sort, SCC)
├── 🌲 Advanced Trees (Segment Trees, Fenwick/BIT, AVL)
├── 🔢 Math & Number Theory (GCD, Modular Arithmetic, Combinatorics)
├── 🪟 Sliding Window & Monotonic Stack/Queue
├── 🔁 Backtracking with Pruning
├── 🔍 Binary Search on Answer
└── 🧵 String Algorithms (KMP, Z-Algorithm, Trie)

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📈 Progress Tracker

Metric	Value
✅ Problems Solved	0 / 100
📅 Current Streak	Active
🏆 Difficulty	Hard
📢 Updates	LinkedIn
⏱️ Avg. Time Per Problem	—

At this level, understanding the "why" behind each solution matters more than the solution itself. Every problem is documented with full reasoning.

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📝 Problem Log

#	Problem	Topic	Key Technique	Solution
01	(Upcoming)	—	—	—
02	(Upcoming)	—	—	—
03	(Upcoming)	—	—	—
...	...	...	...	...
100	(Upcoming)	—	—	—

This table is updated daily. Each entry links to a solution file with full explanation.

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💡 Key Learnings

• Hard problems rarely require exotic algorithms — they require perfect application of fundamentals
• When stuck, reduce the problem: solve for n=1, n=2, find the pattern
• Space-time tradeoffs become critical — memoization vs tabulation, recursion vs iteration
• Drawing the problem visually almost always reveals the approach
• The first accepted solution is never the final solution — always revisit for optimization

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🗂 How to Use This Repo

# Clone the repo
git clone https://github.com/loisekk/100-days-leetcode-phase3.git
cd 100-days-leetcode-phase3

# Navigate to solutions
cd solutions/

# Run any solution
python problem_name.py

Each solution file follows this structure:

Problem Title
─────────────
🔗 LeetCode Link
📌 Approach: <brief explanation>
⏱️ Time Complexity: O(?)
💾 Space Complexity: O(?)
─────────────
[Clean Python Implementation]

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🗺 Full Challenge Journey

Phase	Difficulty	Problems	Status
Phase 1	🟢 Easy	1–100	✅ Completed
Phase 2	🟡 Medium	1–30	🔄 In Progress
Phase 3	🔴 Hard	1–100	🔄 In Progress

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👨‍💻 Author

Yash Brahmankar

"Hard problems don't get easier. You get stronger."

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Made with 🔥 and relentless consistency by Yash Brahmankar