Analysis of Space Complexity:
Definition:
- Space complexity is a measure of the amount of memory space an algorithm requires in relation to the size of the input.
- It provides insights into how the memory requirements of an algorithm increase with the input size.
Notation:
Similar to time
complexity, space complexity is expressed using Big O notation, denoted as
O(f(n)), where "f(n)" represents an upper bound on the growth rate of
the algorithm's memory requirements concerning the input size "n."
Classes of Space
Complexity:
1. O(1) - Constant
Space:
- The memory requirements remain constant
regardless of the input size.
2. O(n) - Linear
Space:
- The memory requirements grow linearly with
the input size.
3. O(n^2) -
Quadratic Space:
- The memory requirements grow quadratically
with the input size.
Example:
For an algorithm
with O(n) space complexity, doubling the input size may approximately double
the memory requirements.
-----------------------------------------------------------------
0 Comments