I don't know about mathematical domain, so this might be off-topic but in some cases a legacy code base that works perfectly can be brittle and full of holes an

I don't know about mathematical domain, so this might be off-topic but in some cases a legacy code base that works perfectly can be brittle and full of holes and bugs that never manifested themselves because the code not directly interfacing the input data is guarded by subset of possible data it should support, and many of the possible code paths have not been evaluated. But if you try to refactor the code to, say support other feature or optimise it, you might get into nastiness that is beyond comprehension, and you cannot count on that the code is coherent or correct. This is my experience for maintaining a legacy base that has been many years in production. It's just a pile of frozen code that nobody has properly refactored probably out of fear for breaking something. This way you end up with unreadable layers and weird technology-specific hacks that were carefully made just work, probably not understanding what the existing code actually did but cargo-culting and resulting with massive amount of code that does little.