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16 lines
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16 lines
1.1 KiB
# Asymptotic Notation |
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The efficiency of an algorithm depends on the amount of time, storage and other resources required to execute the algorithm. The efficiency is measured with the help of asymptotic notations. |
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An algorithm may not have the same performance for different types of inputs. With the increase in the input size, the performance will change. |
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The study of change in performance of the algorithm with the change in the order of the input size is defined as asymptotic analysis. |
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Visit the following resources to learn more: |
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- [@article@Asymptotic Analysis: Big-O Notation and More](https://www.programiz.com/dsa/asymptotic-notations) |
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- [@video@Big O Notation — Calculating Time Complexity](https://www.youtube.com/watch?v=Z0bH0cMY0E8) |
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- [@video@Big O Notation in 5 Minutes](https://www.youtube.com/watch?v=__vX2sjlpXU) |
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- [@video@Asymptotic Notation - CS50](https://www.youtube.com/watch?v=iOq5kSKqeR4) |
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- [@article@CS 61B Lecture 19: Asymptotic Analysis](https://archive.org/details/ucberkeley_webcast_VIS4YDpuP98) |
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- [@article@Big-O Cheat Sheet](https://www.bigocheatsheet.com/)
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