Understanding the Space Complexity of an Algorithm

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[@Mohan-2034]

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[@eghanshith5346]

1.Priori vs. Posterior Analysis: Priori analysis estimates time and memory space before executing an algorithm. Posterior analysis calculates these after execution. We focus on priori analysis for simplicity. 2.Space Complexity Components: Ignore space for source code and simple variables (constants). Consider space for data structures used (e.g., lists). Not applicable here: stack space for recursive algorithms. 3.Example Algorithm: Sum of N Elements: Non-recursive, iterative algorithm. Data structure: list with N elements. Space complexity: O(N) due to list size. Remember, space complexity matters when optimizing memory usage! 🚀

[@talishnaider9575]

Shouldn't space complexity of an algorithm consider only the additional space required by the algorithm beyond the input? the array a was given to us so the complexity should be O(1) no?

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