Computational resources | Computational complexity theory

Space complexity

The space complexity of an algorithm or a computer program is the amount of memory space required to solve an instance of the computational problem as a function of characteristics of the input. It is the memory required by an algorithm until it executes completely. Similar to time complexity, space complexity is often expressed asymptotically in big O notation, such as etc., where n is a characteristic of the input influencing space complexity. (Wikipedia).

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Related pages

NSPACE | Derandomization | NL (complexity) | NTIME | Big O notation | Depth-first search | DTIME | Co-NP | Binary tree | Computational problem | Exponential time hypothesis | L (complexity) | Pseudorandomness | Streaming algorithm | Turing machine | NP (complexity) | DSPACE | Time complexity | RL (complexity) | P (complexity) | Immerman–Szelepcsényi theorem | Algorithm | Savitch's theorem | Space hierarchy theorem | PSPACE