since factorial will have been called recursively with the values 5, 4, 3, 2, 1, and 0, and the return values for each of those will have been stored. If it is then called with a number greater than 5, such as 7, only 2 recursive calls will be made (7 and 6), and the value for 5! will have been stored from the previous call. In this way, memoization allows a function to become more time-efficient the more often it is called, thus resulting in eventual overall speed-up. Some other considerations Functional programming Memoization is heavily used in compilers for functional programming languages, which often use call by name evaluation strategy. To avoid overhead with calculating argument values, compilers for these languages heavily use auxiliary functions called thunks to compute the argument values, and memoize these functions to avoid repeated calculations. Automatic memoization While memoization may be added to functions internally and explicitly by a computer programmer in much the same way the above memoized version of factorial is implemented, referentially transparent functions may also be automatically memoized externally. The techniques employed by Peter Norvig have application not only in Common Lisp (the language in which his paper demonstrated automatic memoization), but also in various other programming languages. Applications of automatic memoization have also been formally explored in the study of term rewriting and artificial intelligence. In programming languages where functions are first-class objects (such as Lua, Python, or Perl), automatic memoization can be implemented by replacing (at run-time) a function with its calculated value once a value has been calculated for a given set of parameters. The function that does this value-for-function-object replacement can generically wrap any referentially transparent function. Consider the following pseudocode (where it is assumed that functions are first-class values): function memoized-call (F is a function object parameter) if F has no attached array values then allocate an associative array called values; attach values to F; end if; if F.values[arguments] is empty then F.values[arguments] = F(arguments); end if; return F.values[arguments]; end function In order to call an automatically memoized version of factorial using the above strategy, rather than calling factorial directly, code invokes memoized-call(factorial(n)). Each such call first checks to see if a holder array has been allocated to store results, and if not, attaches that array. If no entry exists at the position values[arguments] (where arguments are used as the key of the associative