I've been experimenting with a technique for string vectorization: create a "basis space" of N random strings. The vector of string S is `[edist(S, b) for b in

I've been experimenting with a technique for string vectorization: create a "basis space" of N random strings. The vector of string S is `[edist(S, b) for b in basis]` Where edist is some Levenshtein edit distance. You can build feature vectors from these by analyzing adjacency within logical blocks. Take other known Go software, obfuscate it, and vectorize it on the same basis. Even though the obfuscation is random, similar code chunks should project to a similar "shape" manifold.