What does ‘Space Complexity’ mean?
Space Complexity:
The term Space Complexity is misused for Auxiliary Space at many places. Following are the correct definitions of Auxiliary Space and Space Complexity.
Auxiliary Space is the extra space or temporary space used by an algorithm.
Space Complexity of an algorithm is total space taken by the algorithm with respect to the input size. Space complexity includes both Auxiliary space and space used by input.
For example, if we want to compare standard sorting algorithms on the basis of space, then Auxiliary Space would be a better criteria than Space Complexity. Merge Sort uses O(n) auxiliary space, Insertion sort and Heap Sort use O(1) auxiliary space. Space complexity of all these sorting algorithms is O(n) though.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
Recommended Posts:
- Minimize the sum of digits of A and B such that A + B = N
- Multiplication on Array : Range update query in O(1)
- Optimal Strategy for a Game | Special Gold Coin
- Find the coordinates of a triangle whose Area = (S / 2)
- Rearrange array elements such that Bitwise AND of first N - 1 elements is equal to last element
- Maximum prime moves to convert X to Y
- Sum of Digits of the Good Strings
- Count non-adjacent subsets from numbers arranged in Circular fashion
- Minimize sum by dividing all elements of a subarray by K
- Find Range Value of the Expression
- Minimum numbers with one's place as 9 to be added to get N
- Minimum increment or decrement operations required to make the array sorted
- Sum of numbers in a range [L, R] whose count of divisors is prime
- Minimize the cost of partitioning an array into K groups
- Find next greater element with no consecutive 1 in it's binary representation
