Time Complexity

Time Complexity


The computation time taken by a piece of code or an algorithm.

Three types of Asymptotic Notations to express time complexity:

  1. Big-O Notation: Upper Bound
  2. Theta Notation: In between upper and lower bound
  3. Omega Notation: Lower Bound

But generally we used the Big-O Notation to express the time complexity in programming world.

Types of Time Complexity:

  • Constant Time Complexity: O(1)
  • Linear Time Complexity: O(n)
  • Logarithmic Time Complexity: O(log n)
  • Quadratic Time Complexity: O(n²)
  • Exponential Time Complexity: O(2^n)


So, to calculate time complexity, you should count the number of operations in a program. And, No of operations that can be performed in one second by a machine = 10^7

For example,

● Array size = 4*10^7 -> This means you can iterate the array only once. O(N)

solution is needed.

● Array size = 10^3. O(N^2) at max.

● Array size = 10^5. O(N) or O(N log N)

● Array size = 10 O(2^N)

● Matrix N = 1000, M = 1000. Complexity O(N*M).

This is how you can look at the constraint and tell what time complexity will be needed.

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