Computer Science 1 Marks Each

O(log n) denotes logarithmic time complexity. O(log n) represents a code whose execution time will grow logarithmically w.r.t. the size of the input data. O(log n) is typical with algorithms that keep on successively dividing the data range to work upon.

Best case is when the array is sorted in that order, in which we required the array. For example, if we need array elements in ascending order and all the elements of the array is in ascending order.

It is a way to enhance code productivity and quality. It can be achieved by reducing code size and memory, execute statements quickly.

The time taken by the code to execute i.e. the number of iteration or statements is known as time complexity

It is the process where a function calls a itself.