algorithm - What is the asymptotic time complexity of the following piece of code? -

how come big o notation?

float sum = 0 ;      ( int = 1; < n ; i++)     {     sum + = a[i];     }     cout << sum; 

great asked this. went on in class , asked same question. big o notation used describe how efficient or complex algorithm is.

o(1) algorithm execute in same time. efficient type of algorithm. example

bool bigo(string[] big) { if(big[0] == null) {     return false; } return true; } 

there o(n) depend on size of input. example

bool bigo(string[] strings, string value) { for(int = 0; < strings.length; i++) {     if(strings[i] == value)     {         return true;     } } return false; } 

as can tell method can take longer execute depending on input. if strings.length small quick if large length take while.

and there o(n^2). involves multiple loops within self. can o(n^3) depending on how deep nested iterations. example

bool bigo(string[] strings) { for(int = 0; < strings.length; i++) {     for(int j = 0; j < strings.length; j++)     {         if(i == j)          {             continue;         }          if(strings[i] == strings[j])         {             return true;         }     } } return false; } 

now looking @ algorithm think yours is? if said o(n) you're right. big o notation dependent on how efficient algorithm is. efficiency can depend on cpu (time) usage, ,memory usage ,disk usage , network usage