Algorithm Analysis (Time complexity) Software development cycle
-Four phases: 1.Analysis 2.Design Algorithm Design an algorithm to
solve the problem or sub- problem. Algorithm is step by step
problem-solving process, and solution obtained in finite amount of
time. 3.Implementation 4.Testing and Debugging Algorithm Analysis:
The Big-O Notation (contd.) Primitive Operations: -By analyzing a
particular algorithm, we usually count the number of Primitive
Operations: 1. Assigning a value to a variable 2.Calling a function
3.Performing an arithmetic operation 4.Comparing two values
5.Returning from a function The Big-O Notation (contd.) -The
following table shows each of the seven common functions used in
algorithm analysis in order of growth rates. Examples: 1- F(n) = 5n
2 + 3n log n + 2n + 5 We say the function F(n) is O(n 2 ) or Big-O
of n 2 2- F(n)= 3 log n + 2 We say the function F(n) is O(log n) or
Big-O of log n 3- F(n)= 2n log n We say the function F(n) is O(n)
or Big-O of n
constantlogarithmlinearn-log-nquadraticcubicexponential 1log nnn
log nn2n2 n3n3 a n, a>1
