Big O specifically describes the worst-case scenario, and can be used to describe the execution time required or the space used (e.g. in memory or on disk) by an algorithm
The rate of growth of time with respect to input.
https://www.quora.com/What-are-some-easy-ways-to-understand-and-calculate-the-time-complexity-of-algorithms
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