This project shows two recursive implementations of the classic change-making algorithm, which is something we only actually learned out for real today, lol. Choose a mode, then enter a number of cents to make and the kinds of coins that are allowed to be used, separated by spaces. (The algorithm assumes you've got infinitely many of each kind of coin you say!) This was made for a discussion about custom reporters and recursion with @bharvey, @kenny2scratch, and others on GitHub: https://github.com/scratchfoundation/scratch-vm/issues/79 The basic idea is to try out every combination of coins that *might* work to make the amount you want, and then return how many total of those ended up working. The interesting part is that the recursion "forks" into two branches each time - so it has to add the result of the second branch to the result of the first! The two implementations are of the same algorithm, but the approach is a bit different. In "count up", we use a variable that is basically global and increase it by 1 each time we find an amount-matching combination. In "no dynamics", we don't use a variable to keep track of the running total - instead we use a "helper" custom block, which tracks the result of the first branch in an input. Because "count up" works on, well, a variable that's saved globally (either on the stage or the sprite), you can't have two copies of it running at the same time. But "no dynamics" stores its value internally (in a "stack frame" provided by Scratch itself!), using a custom block input as its only memory; this way, you can have two copies of it running at once. Check out @bharvey's awesome project on Snap! visualizing this algorithm: https://snap.berkeley.edu/snap/snap.html#present:Username=bh&ProjectName=count%20change You're much encouraged to see inside and check out the implementations for these two blocks! These are Scratch versions of scripts that @bharvey made in Snap!, and I imagine this recursive algorithm probably dates back centuries (definitely), but we both might be drawing from a beautiful book on programming and computational processes, "Structure and Interpretation of Computer Programs", by Harold Abelson, Gerald Jay Sussman, and Julie Sussman.
