How to Calculate Time Complexity

How to Calculate Time Complexity

What Is Time Complexity? Time complexity describes how the running time of an algorithm changes when the input size grows. It does not measure the exact time in seconds. Instead, it shows how efficiently an algorithm works. For example, an algorithm may take:   1 step for 1 item.   10 steps for 10 items.   1,000 steps for 1,000 items.  This algorithm grows in a direct way. Its time complexity is called O(n). Here, 𝑛 represents the size of the input. What is Big O Notation? Big O notation is used to describe time complexity. It focuses on the general growth of an algorithm and ignores small details, such as: The computer’s speed.  Small constants.  Minor operations.  Exact execution time. Some common time complexities are: Complexity Name Example O(1) Constant Time Accessing an array item O(log ⁡n) Logarithmic Time Binary search O(n) Linear Time Reading every item in a list O(n log⁡ n) Linearithmic Time Efficient sorting O(n 2 ) Quadratic Time Comparing every pair of items O(2 n ) Exponential T…