DSA Problems >>>
Algorithms:
Asymptotic Analysis : Asymptotic Analysis, we evaluate the performance of an algorithm in terms of input size (we don’t measure the actual running time). We calculate, how the time (or space) taken by an algorithm increases with the input size. Such large inputs are never given to software and an algorithm which is asymptotically slower, always performs better for particular situation.
Analysis of Algorithm :
Worst Case : (Big O Notaion) 0 <= f(n) <= cg(n)
Average Case : (theta Notation) 0 <= c1g(n) <= f(n) <= c2g(n)
Best Case :(Omega Notation) 0 <= cg(n) <= f(n)