This particular rope uses the balancing scheme described in the [Purely Functional 1-2 Brother Trees paper authored by Ralph Hinze](https://www.cs.ox.ac.uk/ralf.hinze/publications/Brother12.pdf). It tries to keep the number of nodes to a minimum by joining the strings in adjacent leaf nodes, if joining would not be too expensive.
`rope.sml` contains a rope that tracks line metadata (which has a small performance and memory penalty). This is useful if you have line-based operations in mind.
`tiny_rope.sml` doesn't track line metadata, and is useful when line-queries aren't needed.
Except for the line-based operations `appendLine` and `foldLines`, all functions are the same between the two (aside from `verifyLines` which is just for testing purposes).
I compared the OCaml port with the other text data structures in OCaml, and it beat those handily when processing the datasets from [here](https://github.com/josephg/editing-traces) which just test insertion and deletion. It was also faster at performing substrings than the others.
I don't know other Standard ML libraries to compare it to, but with MLton, this rope implementation beats [the fastest ropes in Rust](https://github.com/josephg/jumprope-rs#benchmarks) at insertion and deletion quite easily, never going 1 ms in the slowest dataset.
I don't know how to explain this result, but I assume most of the credit goes to the MLton compiler. It also seems likely that this is slower on string queries, as those Rust implementations use cache-friendly B-Trees as opposed to the binary tree used here.
