Big O cheatsheat

Big O cheatsheet is a Complete complexity analysis about an algorithm how fast the program is running, how much time taken by the program to give a output How much space required to run certain code or software.

Big O

Big O is a Mathematical notation to describe a function’s limiting behavior when the arguments tend towards a particular value or Infinity. Or simply One can say that Big O is a metric use to describe the efficiency of an algorithm or program.

To describe whether a program is either slower or faster or moderate in terms of execution time and how a program performs in its worst case. Big O is also called asymptotic runtime.

Different ways to describe the runtime of an Algorithm

In actual case to describe the runtime of an algorithm there are three different ways:-

  1. Best Case → Big Ω → Lower Bound
  2. Worst Case → Big O → Upper Bound
  3. Expected Case → Big Θ → Tight Bound

time and space Complexity

To be clear about Big O one certainly need to know about time and space complexity. Why one should be required to analyze time and space.