What you said is not very correct too! Big O tells about the "order of Growth of a function or the Growth rate", that's it. It gives a larger view of the functi

What you said is not very correct too! Big O tells about the "order of Growth of a function or the Growth rate", that's it. It gives a larger view of the function. Seeing from 1000 feet above the ground. Link: http://web.mit.edu/16.070/www/lecture/big_o.pdf http://web.mit.edu/16.070/www/lecture/big_o.pdf My understanding -- A bounding function is when we know the exact function and its end-points from an algorithm. We know the extremes. i.e C1 and C2. i.e a Function falls within that boundary, it will always stay within that box(end-points). C1 and C2 are 2 lines, making a rectangle. - Worst case, Best case, average case are different input cases, under which the algorithm grows in different ways. And we use BigO notation to classify them under easier functions, based on the order of Growth of a function. And unless we don't know that exact function, its not possible to predict for any input variables. So don't call Big O as any bounding function, unless we know c1 and c2 <end bounds>. - Big O is a notation that characterizes functions according to their growth rates. - Different functions with the same growth rate may be represented using the same O notation. - The letter O is used because the growth rate of a function is also referred to as order of the function. A description of a function in terms of big O notation usually only provides an upper bound on the growth rate of the function.