✨💻LeetCode Top Interview 150 Solutions 💻✨

Welcome to my LeetCode Top Interview 150 repository! 🚀

☘️ This repository contains my solutions to the LeetCode Top Interview 150 coding problems.

☘️ I've tackled a variety of algorithmic challenges that cover essential data structures, algorithms, and problem-solving techniques for coding interviews.

📂 File Structure:

✅ Each file is named according to the problem number for easy navigation (e.g Prob1.java which stands for problem no. 1: two sum problem).

✅ I've included detailed comments in each solution to explain the thought process, logic and algorithm used.

✅ This should help in understanding the approach and implementing solutions more quickly and easily!

🔍 How to Search for Solutions:

📌 You can search by problem number to find the solution you're looking for.

📌Files are stored in dictionary order.

⌨️ Tech Stack:

🌟 Language: Java

🌟 Concepts Covered: Data Structures, Algorithms, Programming Logic

📚 Data Structures and Algorithms Covered:

Here are the data structures and algorithms that I have worked on and implemented:

• 🧱 Arrays: Efficient storage and access of elements.
• 🔤 Strings: Manipulating and processing sequences of characters.
• 🔑 HashMap: Key-value storage and retrieval for fast lookups.
• 🌳 Trees:
  • 🌿 Binary Trees
  • 🌲 Binary Search Trees (BST)
• 🔗 Linked Lists:Solved linked list problems using various pointer approaches.
• 🗂️ Stacks: LIFO (Last In First Out) operations for managing function calls and expressions.
• 💡 Bit Manipulation: Efficiently working with binary data.
• ➗ Math: Implementing mathematical algorithms and logic.
• 🧮 1D Dynamic Programming (DP): Optimizing solutions using subproblem solutions.
• 🌬️ Sliding Window: Efficiently solving range-based problems.
• ↔️ Two Pointers: Efficient techniques for searching and manipulation in arrays or lists.
• 🐢🐇 Fast and Slow Pointer: Detecting cycles or solving linked list problems.
• 🌀 Divide and Conquer: Breaking problems into subproblems for efficient solutions.
• ♟️ Backtracking: Recursively solving problems by exploring all possible solutions.
• ➡️ Forward Pass: Processing data from start to end.
• ⬅️ Backward Pass: Processing data from end to start.
• 📈 Kadane's Algorithm: Maximum subarray sum.
• 🕸️Graph Data Structure: Nodes connected by edges, forming a network. 📍➖📍➖📍

🏆 Why This Repo?:

This repo serves as:

🌟 My personal coding journal to keep track of solved problems.

🌟 A resource for anyone preparing for coding interviews or practicing their problem-solving skills.

🌟 A showcase of clean, optimized, and well-commented code.

🎯Improvements and Feedback:

I'm continuously improving my solutions and making them more efficient. Feel free to:

🌟 Open an issue or create a pull request for suggestions.

🌟 Share feedback if you spot any improvements or optimizations!

Happy coding! 🎉