Month 4 · Week 16 of 40

Sorting Algorithms & Binary Search

Divide, conquer, and sort at maximum speed.

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Week Overview

Learn why O(n log n) is the theoretical lower bound for comparison sorting. Implement Merge Sort, QuickSort with partitioning, and logarithmic Binary Search.

Core Concepts & Topics

Divide-and-Conquer Paradigm
Merge Sort Implementation & Stability
QuickSort with Lomuto & Hoare Partitioning
Binary Search on Rotated Sorted Arrays
Algorithm Optimization Strategies
Hands-On Challenge

Week 16 Project: High-throughput sorting benchmark suite comparing O(n^2) and O(n log n) algorithms.

Every week at DoxaTech Hub requires submitting real working code tested by our automated grading suite. You will push code to your personal GitHub repository, open pull requests, and receive instant feedback.

Frequently Asked Questions

Why is QuickSort preferred over MergeSort in practice?

QuickSort operates in-place without requiring extra temporary arrays (O(1) auxiliary space), offering better CPU cache locality.

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Week 15: Stacks, Queues & Hash Tables
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Week 17: Python Basics & Control Flow
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Month 4 Modules

This week is part of Data Structures & Algorithms.

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