Space complexity refers to the amount of memory space required by an algorithm in relation to the size of the input data. It is a function, often denoted as S(N), that represents the number of fixed-size memory units used by the algorithm for an input of size N. For example, if an algorithm needs to create a new array that is the same size as the input array, its space complexity would be linear, or O(N), where N is the size of the input array. This term is crucial in evaluating the efficiency of an algorithm, especially when working with large data sets or in systems with limited memory resources.
[References: The definition and explanation of space complexity can be found in various educational resources and literature on data structures and algorithms, such as computer science textbooks and online educational platforms12., , ]
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