A recursive method calls itself. This can continue forever, until stack space is exhausted. Ruby supports recursive methods.
Here we implement a method that determines all possible ways to count change for a certain amount. It does not find just one solution. It finds all solutions.
This program requires two initial arrays: an array of coins (which is at first empty) and an array of amounts. The "amounts" array stores the number of cents each coin is worth.
Change()
is the recursive method. It first checks whether we have reached our goal amount. It tries to add coins and then calls itself.def change(coins, amounts, highest, sum, goal) # Display result if we have correct change. if sum == goal display(coins, amounts) end # Return if we have too much money. if sum > goal return end # Loop over coin amounts and try adding them. amounts.each do |value| if value >= highest # Copy the coins array, add value to it. copy = Array[] copy.concat coins copy.push(value) # Recursive call: add further coins if needed. change(copy, amounts, value, sum + value, goal) end end end def display(coins, amounts) # Display all the coins. amounts.each do |amount| count = 0 coins.each do |coin| if coin == amount count += 1 end end print amount, ": ", count, "\n" end print "\n" end # Specify our starting coins and all coin amounts. coins = Array[] amounts = Array[1, 5, 10, 25, 50] # Make change for 51 cents. change(coins, amounts, 0, 0, 51)1: 51 5: 0 10: 0 25: 0 50: 0 1: 46 5: 1 10: 0 25: 0 50: 0 1: 41 5: 2 10: 0 25: 0 50: 0 1: 41 5: 0 10: 1 25: 0 50: 0...
In change, important things happen. The coins array is copied into a "copy" array. We use the concat method for this, and then push our new value into the array.
In the output, we see ways to make 51 cents. We can use 51 one-cent pieces. Or we can use 46-one cent pieces and 1 five-cent piece. If you run the program, the output has all possibilities.
With this example from the Structure
and Interpretation of Computer Programs, we consider a problem that is not trivial. Yet many real-world problems are much more complex.