The schematics for the older versions of the SuperMemo algorithm (SM-2 and SM-5) have been published but they're quite old and any good reimplementation is actually a fork that fixes glaring deficiencies in the old algorithms.
The newest versions (SM-19) are proprietary and rely on a bunch of training data (they use some kind of ML) gathered from SuperMemo users (there is a way to get access to SuperMemo algorithm but you have to negotiate a license from memory). There is some rough outline of the algorithms on the SuperMemo wiki, but you couldn't reimplement it any more than you could reimplement Google Search given the Wikipedia description of PageRank.
Sorry I meant SM-18 (released in 2019, hence the confusion). But for completeness the only information available on SM-17 is one of two incredibly long articles written by Piotr Wozniak[1,2]. SM-18 is only a minor improvement over SM-17, with some changes to how difficulty is calculated[3].
The newest versions (SM-19) are proprietary and rely on a bunch of training data (they use some kind of ML) gathered from SuperMemo users (there is a way to get access to SuperMemo algorithm but you have to negotiate a license from memory). There is some rough outline of the algorithms on the SuperMemo wiki, but you couldn't reimplement it any more than you could reimplement Google Search given the Wikipedia description of PageRank.