In the context of complexity analysis, the term case refers to the scenario in which the algorithm performs exceptionally well.
The best case complexity is often used to describe the best possible of an algorithm under certain conditions.
The best case complexity of an algorithm refers to the amount of time or space it can take to execute.
Worst-case time complexity
What does it mean when an algorithm has a time complexity of O(1)?
What does it mean when an algorithm has a space complexity of O(n)?
What does O(log n) time complexity mean?
average case
worst case
When analyzing the complexity of an algorithm, we often use the notation , which represents an upper bound on the growth rate of the algorithm's time or space requirements.
Best-case time complexity
The complexity of an algorithm describes the total amount of time it takes to run.
space complexity
O(n)
Which of the following is the best time complexity?
The case complexity gives us an idea of how the algorithm performs on inputs that are representative of real-world scenarios.
The worst case complexity of an algorithm refers to the amount of time it can take to execute.
