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Factorial algorithms encompass a diverse array of computational techniques, with their effectiveness and practical applicability contingent on the precise methodologies employed within the chosen programming language's implementation process. Among these methodologies, the iterative approach has demonstrated noteworthy efficiency. Nevertheless, the optimization of factorial computations can be elevated by leveraging advanced algorithms specifically tailored to unique computational demands. In contrast to the recursive paradigm, which boasts conceptual simplicity, it remains susceptible to the drawback of redundant calculations and substantial memory requisites. This superfluousness can be efficiently eradicated through the utilization of the iterative algorithm, thereby furnishing a more expeditious solution within the domain of factorial computations. This paper elaborates on the implementations of all scenarios in a manner that comprehensively addresses both the temporal complexity and memory constraints, particularly when dealing with substantial sample values.
Nair et al. (Fri,) studied this question.