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:-
- Best Case → Big Ω → Lower Bound
- Worst Case → Big O → Upper Bound
- 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.