DSA Mastery: From Fundamentals to Algorithm Dominance

A structured, pattern-based curriculum to master Data Structures and Algorithms for FAANG interviews and competitive programming.

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Learning Philosophy

This curriculum is built on one core principle: pattern recognition beats memorization.

Every algorithm problem is a combination of known patterns. Master the patterns, and you can solve any problem — even ones you've never seen before.

flowchart LR
    A["Learn Pattern"] --> B["Recognize Pattern\nin New Problems"]
    B --> C["Apply & Adapt"]
    C --> D["Combine Patterns\nfor Hard Problems"]
    D --> E["Algorithm\nMastery"]

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Who This Is For

• Senior engineers preparing for FAANG-level algorithm interviews
• Developers who want structured, systematic algorithm training
• Competitive programming aspirants building their pattern library
• Anyone who knows C# or TypeScript and wants to think algorithmically

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Repository Structure

AdvanceDataStructureAlgorithm/
│
├── docs/                          # Foundation documents
│   ├── algorithm-thinking.md      # Mental framework for problem solving
│   ├── complexity-analysis.md     # Big-O mastery guide
│   ├── pattern-recognition.md     # Pattern identification system
│   └── interview-strategy.md      # 45-minute interview game plan
│
├── patterns/                      # Core pattern library (20 patterns)
│   ├── 01_two_pointers/          # Sorted arrays, pair finding
│   ├── 02_sliding_window/        # Contiguous subarrays/substrings
│   ├── 03_fast_slow_pointer/     # Cycle detection, linked lists
│   ├── 04_binary_search/         # Search spaces, optimization
│   ├── 05_prefix_sum/            # Range queries, cumulative ops
│   ├── 06_monotonic_stack/       # Next greater/smaller element
│   ├── 07_heap_priority_queue/   # Top-K, merge-K, median
│   ├── 08_backtracking/          # Combinations, permutations
│   ├── 09_dynamic_programming/   # Optimization, counting
│   ├── 10_greedy/                # Local optimal = global optimal
│   ├── 11_graph_traversal/       # BFS, DFS, shortest paths
│   ├── 12_union_find/            # Dynamic connectivity
│   ├── 13_topological_sort/      # Dependency ordering
│   ├── 14_trie/                  # Prefix matching
│   ├── 15_segment_tree/          # Range queries with updates
│   ├── 16_fenwick_tree/          # Binary indexed tree
│   ├── 17_bit_manipulation/      # Bitwise tricks
│   ├── 18_divide_and_conquer/    # Split, solve, combine
│   ├── 19_advanced_dp/           # Bitmask, interval, digit DP
│   └── 20_advanced_graph/        # Dijkstra, MST, flow
│
├── practice/                      # Curated problem sets
│   ├── easy/                     # 20 problems — build confidence
│   ├── medium/                   # 30 problems — build speed
│   └── hard/                     # 25 problems — build mastery
│
└── README.md                     # This file

Each pattern folder contains:

• concept.md — Theory, intuition, and templates
• visual.md — Mermaid diagrams for visual learners
• problems.md — Curated problems with step-by-step solutions
• csharp/ — Clean C# implementations
• typescript/ — Clean TypeScript implementations

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Learning Roadmap

Phase 1: Foundations (Weeks 1-2)

Build the mental framework before diving into patterns.

flowchart TD
    A["Algorithm Thinking\n(docs/algorithm-thinking.md)"] --> B["Complexity Analysis\n(docs/complexity-analysis.md)"]
    B --> C["Pattern Recognition\n(docs/pattern-recognition.md)"]
    C --> D["Interview Strategy\n(docs/interview-strategy.md)"]
    D --> E["Ready for Patterns"]

    style E fill:#00cc00,color:#000

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Goal: Understand the 5-step problem-solving framework, master Big-O analysis, and learn the pattern recognition decision tree.

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Phase 2: Core Patterns (Weeks 3-8)

Learn one pattern at a time. For each pattern: read concept → study visuals → solve 3-5 problems.

flowchart TD
    subgraph "Week 3-4: Array Patterns"
        P1["01 Two Pointers"] --> P2["02 Sliding Window"]
        P2 --> P3["03 Fast & Slow"]
        P3 --> P4["04 Binary Search"]
        P4 --> P5["05 Prefix Sum"]
    end

    subgraph "Week 5-6: Stack, Heap, Recursion"
        P6["06 Monotonic Stack"] --> P7["07 Heap"]
        P7 --> P8["08 Backtracking"]
    end

    subgraph "Week 7-8: DP & Greedy"
        P9["09 Dynamic Programming"] --> P10["10 Greedy"]
    end

    P5 --> P6
    P8 --> P9

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Goal: Recognize and apply each pattern independently. Solve easy/medium problems for each.

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Phase 3: Graph & Advanced DS (Weeks 9-12)

flowchart TD
    subgraph "Week 9-10: Graph Fundamentals"
        P11["11 Graph Traversal"] --> P12["12 Union-Find"]
        P12 --> P13["13 Topological Sort"]
    end

    subgraph "Week 11-12: Advanced Data Structures"
        P14["14 Trie"] --> P15["15 Segment Tree"]
        P15 --> P16["16 Fenwick Tree"]
    end

    P13 --> P14

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Goal: Handle graph problems confidently. Know when to use specialized data structures.

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Phase 4: Expert Level (Weeks 13-16)

flowchart TD
    subgraph "Week 13-14: Advanced Techniques"
        P17["17 Bit Manipulation"] --> P18["18 Divide & Conquer"]
        P18 --> P19["19 Advanced DP"]
    end

    subgraph "Week 15-16: Competition Level"
        P20["20 Advanced Graph"] --> MIXED["Mixed Hard Problems"]
    end

    P19 --> P20

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Goal: Solve hard problems that combine multiple patterns. Competitive programming readiness.

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Phase 5: Interview Readiness (Weeks 17-20)

flowchart LR
    A["Timed Practice\n(25 min per medium)"] --> B["Mock Interviews\n(45 min sessions)"]
    B --> C["Weak Area Review\n(revisit tough patterns)"]
    C --> D["Daily 1 Problem\n(maintain sharpness)"]
    D --> E["Interview Ready"]

    style E fill:#00cc00,color:#000

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Quick Pattern Reference

Use this table when you encounter a new problem:

Signal	Pattern	Section
Sorted array, find pair	Two Pointers	01
Contiguous subarray/substring	Sliding Window	02
Linked list cycle	Fast & Slow	03
Search in sorted / minimize max	Binary Search	04
Range sum queries	Prefix Sum	05
Next greater/smaller	Monotonic Stack	06
Top K / merge K	Heap	07
Generate all possibilities	Backtracking	08
Count ways / min cost / feasibility	DP	09
Local optimal = global optimal	Greedy	10
Shortest path / connected components	Graph	11
Dynamic connectivity / merge groups	Union-Find	12
Dependency ordering	Topological Sort	13
Prefix matching / autocomplete	Trie	14
Range query + updates	Segment Tree	15
Prefix sum + updates (simpler)	Fenwick Tree	16
XOR tricks / subset enum	Bit Manipulation	17
Split, solve halves, combine	Divide & Conquer	18
Bitmask/interval/digit state	Advanced DP	19
Weighted shortest path / MST	Advanced Graph	20

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Complexity Cheat Sheet

n ≤ 10        → O(n!) or O(2^n)   → Brute force / backtracking
n ≤ 20        → O(2^n)            → Bitmask DP / meet in middle
n ≤ 100       → O(n^3)            → Floyd-Warshall / cubic DP
n ≤ 1,000     → O(n^2)            → Nested loops / 2D DP
n ≤ 100,000   → O(n log n)        → Sorting / segment tree
n ≤ 1,000,000 → O(n)              → Hash map / two pointers
n ≤ 10^12     → O(log n)          → Binary search / math

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How to Use This Repository

1. Start with docs/ — Read all four foundation documents
2. Work through patterns/ sequentially — Each pattern builds on previous ones
3. For each pattern:
   • Read concept.md for theory
   • Study visual.md for diagrams
   • Solve problems in problems.md
   • Study implementations in csharp/ and typescript/
4. Practice with practice/ — Start easy, progress to hard
5. Review regularly — Revisit patterns you find difficult

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Languages

All implementations are provided in:

• C# — Using modern C# (.NET 6+) idioms
• TypeScript — Using strict TypeScript with proper typing

Both languages are interview-ready and cover the same algorithms with language-appropriate patterns.

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Built for engineers who refuse to leave algorithm performance to chance.