Can you explain best-case and worst-case time complexity with examples?
Sure! Best-case time complexity refers to the minimum time an algorithm takes to complete, while worst-case is the maximum time.
Can you give me an example of each?
Absolutely! For example, in a linear search, the best-case occurs when the target is the first element, O(1). The worst-case is O(n) when the target is the last element or not present.
What about sorting algorithms?
For bubble sort, the best-case is O(n) when the array is already sorted, and the worst-case is O(n^2) when it's in reverse order.
How do these complexities affect performance?
They help predict how algorithms will perform under different conditions, guiding the choice of the most efficient algorithm for a task.
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