The Big O Trivia

The Big O Trivia

Often while looking at the way a program would be executed especially those involving multiple loops and heavy data processing, developers could be seen talking about complexity using the term known as Big O.

To understand let us look at the academic topics about time complexity. One could vividly remember about Big O, Big Θ and Big Ω. Going by the textbook definitions these could be summarized as

O: Big O describes an upper bound on time Ω: Big Ω describes the lower bound on time Θ: Big Θ means both O and Ω i.e., an algorithm is Big(Θ) if it is both O and Ω

Now coming back to the developer discussion why would one refer to big O(which is upper bound) rather than big Ω(the lower bound) or the big Θ(the tight bound).

To answer this, one has to understand that the industry people have merged the O and Θ and since the focus is more about the worst case scenario big O is used to denote the complexity.