Calculation of storage complexity, Data Structure & Algorithms

Since memory is becoming more & cheaper, the prominence of runtime complexity is enhancing. However, it is very much significant to analyses the amount of memory utilized by a program. If the running time of any algorithms is not good then this will take longer to execute. However, if this takes more memory (the space complexity is more) beyond the capacity of the machine then the program will not execute at all. Therefore it is more critical than run time complexity. However, the matter of respite is that memory is reutilized throughout the course of program execution.

We will analyses this for recursive & iterative programs.

For an iterative program, usually this is just a matter of looking at the variable declarations and storage allocation calls, for example number of variables, length of an array etc.

The analysis of recursive program w.r.t. space complexity is more complexes as the space utilized at any time is the total space used through all recursive calls active at that time.

Each of recursive call takes a constant amount of space & some space for local variables and function arguments, and for remembering also some space is allocated where each call must return to. General recursive calls employ linear space. That is, for n recursive calls, the space complexity is O(n).

Assume the following example: Binary Recursion (A binary-recursive routine (potentially) calls itself twice).

A.    If n equals 0 or 1, then return 1

B.     calculate recursively f (n-1)

C.     calculate recursively f (n-2)

D.    Return the total of the results from steps 2 and 3.

Posted Date: 4/4/2013 6:10:43 AM | Location : United States







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