Algorithms For Dummies

 

   

  PART 1 

 Getting Started

Many possible functions can result in worse results, but the choice of functions 

offered by the Big O notation that you can use is restricted because its purpose is 

to simplify complexity measurement by proposing a standard. Consequently, this 

section contains just the few functions that are part of the Big O notation. The fol-

lowing list describes them in growing order of complexity:

 

»

Constant complexity O(1): The same time, no matter how much input you 

provide. In the end, it is a constant number of operations, no matter how long 

the input data is. This level of complexity is quite rare in practice.

 

»

Logarithmic complexity O(log n): The number of operations grows at a 

slower rate than the input, making the algorithm less efficient with small 

inputs and more efficient with larger ones. A typical algorithm of this class is 

the binary search, as described in Chapter 7 on arranging and searching data.