The case complexity of an algorithm refers to the expected amount of time it takes to execute for inputs of typical size.
Best-case time complexity
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.
Worst-case time complexity
O(log n)
Time complexity
notation provides a way to express the upper bound of an algorithm's time or space complexity in a simple and concise manner.
best case
The complexity of an algorithm describes the total amount of memory space it requires.
The case complexity is important because it guarantees that the algorithm will not perform worse than a certain threshold.
In the context of complexity analysis, the term case refers to the scenario in which the algorithm performs exceptionally well.
Which of the following is the best time complexity?
What does it mean when an algorithm has a time complexity of O(1)?
Average-case time complexity
An algorithm's efficiency can be measured by its complexity and its space complexity.
What does it mean when an algorithm has a space complexity of O(n)?
What does O(1) time complexity mean?
The complexity of an algorithm describes the total amount of time it takes to run.
In the context of algorithm complexity, what does the term 'best-case' refer to?
