What does O(n) represent in Big O Notation?*0/1a. Constant time complexityb. Linear time complexityQuadratic time complexity

Understanding O(n) in Big O Notation

1. Definition of Big O Notation: Big O notation is a mathematical representation used to describe the upper bound of the time complexity of an algorithm. It characterizes the performance of an algorithm in terms of input size (n).

2. What O(n) Represents: The notation O(n) specifically indicates that the time complexity increases linearly with the size of the input. This means that if the size of the input data doubles, the time it takes to complete the operation will also double.

3. Options Analysis:

   • a. Constant time complexity: Incorrect, as this is represented by O(1).
   • b. Linear time complexity: Correct, as O(n) describes an algorithm whose time complexity grows linearly with the input size.
   • c. Quadratic time complexity: Incorrect, as this is represented by O(n²).

Final Answer

O(n) represents Linear time complexity (Option b).