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CO2412 Computational Thinking Lecture 5 Notes

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This document contains detailed notes from Lecture 5 of the CO2412 course on Computational Thinking. The lecture provides a comprehensive review of Big O notation, a crucial concept for estimating the time and space efficiency of algorithms, particularly in worst-case scenarios. The notes focus on simplifying complexity estimations by highlighting the fastest-growing terms and discarding less significant details.

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CO2412: Computational Thinking
Lecture 5

Review of Big O Notation
1. Big O Notation Recap
o Big O notation is used to estimate the time (and space) efficiency of
algorithms, focusing on the worst-case scenario. It simplifies the
estimation by keeping only the fastest-growing term and discarding
all other details.
Sorting Algorithms Overview
1. Bubble Sort
o Complexity: O(n²)

o How It Works:

 Repeatedly steps through the list.
 Compares adjacent elements and swaps them if they are in
the wrong order.
 Each pass through the list places the next largest element in
its correct position.
Example:

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