Enhancing Ropes for Collaborative Text Editing

Rope is a tree-based data structure providing performance enhancements in string concatenation operations in applications such as text editors. Even though collaborative text editing has become one of the major applications in cloud environments, utilizing ropes in collaborative text editing is rarely discussed in current literature. In this study, we enhance the Rope data structure for collaborative text editing. Firstly we discuss possible issues that Ropes may suffer in collaborative text editing and propose enhancements that adapt Ropes to such environments. During this adaptation we pay special attention to keep Ropes' immutable nature for the insert operations and balance the tree by following AVL-tree-style and Red-Black-Tree-style methods. We also provide a performance comparison of those balancing approaches. In our results, it can be seen that the AVL-Rope and Red-Black-Rope are slower in the concatenation operation due to balancing, but faster in index search operation and insert operation than the unbalanced Rope.