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What does O(log n) time complexity mean?
O(1)
The
complexity of an algorithm describes the total amount of time it takes to run.
worst case
O(n)
The
case complexity of an algorithm refers to the expected amount of time it takes to execute for inputs of typical size.
The worst case complexity of an algorithm refers to the
amount of time it can take to execute.
The
complexity of an algorithm describes the total amount of memory space it requires.
Average-case time complexity
In the context of algorithm complexity, what does the term 'best-case' refer to?
space complexity
In the context of complexity analysis, the term
case refers to the scenario in which the algorithm performs exceptionally well.
O(log n)
The best case complexity is often used to describe the best possible
of an algorithm under certain conditions.
The average case complexity is useful for understanding how the algorithm is likely to perform on
inputs.
An algorithm's efficiency can be measured by its
complexity and its space complexity.
Big O notation
best case
The
case complexity gives us an idea of how the algorithm performs on inputs that are representative of real-world scenarios.
Time complexity
