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Algorithmic & Quantitative Interview Preparation

πŸ“Œ Objective

This repository contains my optimized C++ solutions for standard algorithmic interview questions, primarily following the NeetCode 150 and Blind 75 roadmaps.

My focus is on writing clean, production-grade C++ code with strict attention to time and space complexity, memory management, and edge-case handling.

🧠 Methodology

Each solution in this repository is treated as a professional code submission. I prioritize:

  • Optimal Big O Complexities: Avoiding brute-force nested loops in favor of Hash Maps, Two Pointers, and Sliding Window techniques.
  • Modern C++ Standards: Utilizing std::unordered_map, std::vector, and standard library algorithms for efficient data retrieval.
  • Documentation: Every file includes a header detailing the exact Time Complexity, Space Complexity, and a brief explanation of the algorithmic strategy.

πŸ“ Repository Structure

The repository is strictly organized by core algorithmic patterns to build a modular understanding of data structures:

  • /01_Arrays_and_Hashing - (Focus on constant-time lookups)
  • /02_Two_Pointers - (Focus on in-place array/string manipulation)
  • /03_Sliding_Window - (Focus on continuous sub-arrays)
  • /04_Stack - (Focus on LIFO operations)
  • (More sections will be added as I progress through the curriculum)

πŸš€ Current Focus

I am currently mastering Arrays and Hashing, building muscle memory for std::unordered_set and std::unordered_map to achieve $O(N)$ time complexity on array traversal problems.


Continuously building foundations for High-Frequency Trading (HFT) and Software Engineering roles.

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Optimal C++ solutions for NeetCode 150 & Blind 75, focused on Big-O performance and C++ STL memory efficiency for Quant & SWE roles.

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