Skip to content

A complete collection of essential Data Structures & Algorithms patterns with clean, well-explained code examples to master problem-solving code examples to master problem-solving and crack MAANG interviews. Covers core patterns like Sliding Window,Two Pointers,DP, Graphs and Backtracking with templates,complexity notes and practical interview tips

License

Notifications You must be signed in to change notification settings

pawan-cpu/Data-Structure-Algorithms-Patterns

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Data-Structure-Algorithms-Patterns

A complete collection of essential Data Structures & Algorithms patterns with clean, well-explained code examples to master problem-solving code examples to master problem-solving and crack MAANG interviews. Covers core patterns like Sliding Window,Two Pointers,DP, Graphs and Backtracking with templates,complexity notes and practical interview tips

🚀 Data Structures & Algorithms – Crack MAANG & Top Tech Interviews

Stars Forks Issues License MAANG Companies


🧭 Table of Contents

  1. About the Repository
  2. Core Concepts
  3. Popular DSA Patterns
  4. MAANG-Level Problem Set
  5. Company-Wise Patterns
  6. Contributing
  7. Resources & References
  8. Author

📘 About the Repository

This repository is a comprehensive collection of essential Data Structures & Algorithms (DSA) patterns, designed to help you master problem-solving and crack interviews at MAANG, Swiggy, Zomato, and top startups.

Each pattern comes with:

  • 🧩 Code templates in Python, C++, or Java
  • 🧠 Explanation of core logic
  • ⏱️ Time and Space Complexity
  • 🏹 Real-world interview problems

⚙️ Core Concepts

Before diving into patterns, review these fundamental areas:

  • Arrays & Strings
  • Recursion & Backtracking
  • Linked Lists, Stacks, Queues
  • Trees & Graphs
  • Dynamic Programming
  • Sorting & Searching
  • Greedy Algorithms
  • Bit Manipulation

💡 Popular DSA Patterns

Pattern Description Example Problems
🪟 Sliding Window Optimize subarray problems for max/min/sum/k-length Longest Substring Without Repeating Characters (LeetCode #3), Max Consecutive Ones, Minimum Window Substring
🎯 Two Pointers Works on sorted data to find pairs, partitions 3Sum, Container With Most Water, Remove Duplicates from Sorted Array
🧮 Binary Search Efficient searching or optimization Search Rotated Array, Find Peak Element, Median of Two Sorted Arrays
🧵 Fast & Slow Pointers Detect loops or middle nodes Linked List Cycle, Palindrome Linked List
🔁 Dynamic Programming Break down complex problems into subproblems Longest Increasing Subsequence, House Robber, Coin Change
🌳 Trees & Graphs (DFS/BFS) Hierarchical and connected data traversal Binary Tree Level Order, Clone Graph, Word Ladder
🎲 Backtracking Generate all combinations or paths N-Queens, Sudoku Solver, Permutations
🧭 Greedy Local optimal → global optimal Jump Game, Interval Scheduling, Huffman Encoding
🧮 Prefix Sum / Kadane’s Efficient range calculations Maximum Subarray, Subarray Sum Equals K
🧱 Stack & Monotonic Stack Useful in range problems Largest Rectangle in Histogram, Daily Temperatures

🔥 MAANG-Level Problem Set

🟠 Sliding Window

  • Longest Substring Without Repeating CharactersGoogle, Amazon
    👉 Use hash map to track characters; move window start as duplicates appear.
    ⏱ O(N)
  • Minimum Window SubstringMeta, Microsoft
    👉 Maintain counts of target chars and shrink window.
    ⏱ O(N)

🔵 Two Pointers

  • Container With Most WaterAmazon, Netflix
    👉 Use pointers at both ends; move smaller height inward.
    ⏱ O(N)
  • 3Sum ProblemGoogle, Meta
    👉 Sort + Two Pointers from both ends to find zero-sum triplets.
    ⏱ O(N²)

🟢 Dynamic Programming

  • Coin ChangeAmazon, Meta
    👉 Classic DP to find min coins for target sum.
    ⏱ O(N * amount)
  • Longest Increasing SubsequenceGoogle, Netflix
    👉 Use DP with binary search for O(N log N).

🟣 Graphs

  • Word LadderGoogle, Swiggy
    👉 BFS transformation sequence between words.
    ⏱ O(N * L²)
  • Clone GraphMeta
    👉 DFS clone with hash map to prevent duplication.

🔴 Backtracking

  • N-QueensAmazon, Zomato
    👉 Recursive placement with column and diagonal checks.
    ⏱ O(N!)
  • PermutationsNetflix, Google
    👉 Swap and explore recursively.
    ⏱ O(N!)

⚫ Greedy

  • Jump GameAmazon
    👉 Track maximum reachable index at each step.
    ⏱ O(N)
  • Activity SelectionZomato, Swiggy
    👉 Sort by end times; pick non-overlapping activities.
    ⏱ O(N log N)

🏢 Company-Wise Patterns

Company Common Patterns Example Problems
Amazon Sliding Window, Greedy, Trees LRU Cache, Jump Game, Binary Tree Zigzag
Google Graphs, DP, Backtracking Word Ladder, N-Queens, LIS
Meta Two Pointers, Hashing, DP 3Sum, Clone Graph, Coin Change
Netflix Binary Search, Greedy Container With Most Water, Meeting Rooms II
Swiggy Graphs, Greedy, BFS Minimum Path Delivery, Word Ladder
Zomato DP, Sorting, Greedy Restaurant Allocation, Activity Scheduling

📚 Resources & References


🤝 Contributing

Contributions are welcome!

  1. Fork this repository
  2. Create a new branch (feature/new-pattern)
  3. Add explanations or code samples
  4. Submit a pull request 🚀

👨‍💻 Author

Pawan Kumar
📍 Product Manager | Data & DevOps Mentor | AI & Cloud Enthusiast
🔗 LinkedIn
✉️ pawankm7654@gmail.com


Star this repository if it helped you — it motivates to add more curated interview content every week!

About

A complete collection of essential Data Structures & Algorithms patterns with clean, well-explained code examples to master problem-solving code examples to master problem-solving and crack MAANG interviews. Covers core patterns like Sliding Window,Two Pointers,DP, Graphs and Backtracking with templates,complexity notes and practical interview tips

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published