Analysis of Space Complexity:

 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.

 

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