The average case complexity is useful for understanding how the algorithm is likely to perform on inputs.
What does O(n) time complexity mean?
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.
The case complexity gives us an idea of how the algorithm performs on inputs that are representative of real-world scenarios.
Best-case time complexity
The complexity of an algorithm describes the total amount of time it takes to run.
The complexity of an algorithm describes the total amount of memory space it requires.
An algorithm's efficiency can be measured by its complexity and its space complexity.
The best case complexity is often used to describe the best possible of an algorithm under certain conditions.
O(1)
What does it mean when an algorithm has a space complexity of O(n)?
best case
In the context of algorithm complexity, what does the term 'best-case' refer to?
The case complexity of an algorithm refers to the expected amount of time it takes to execute for inputs of typical size.
The best case complexity of an algorithm refers to the amount of time or space it can take to execute.
space complexity
What does O(1) time complexity mean?
notation provides a way to express the upper bound of an algorithm's time or space complexity in a simple and concise manner.
