Hone logo
Hone
Problems

Implementing Operational Transformation for Real-time Collaborative Editing in React

This challenge focuses on building a core component of collaborative editing systems: Operational Transformation (OT). You will implement an OT system within a React application to handle concurrent edits from multiple users to a single document in real-time. This is fundamental for applications like Google Docs or Figma, enabling seamless collaboration.

Problem Description

Your task is to create a React component that manages a shared document state using an Operational Transformation algorithm. This component should be able to:

  1. Receive and apply operations: Handle incoming operations (insertions, deletions) from different users.
  2. Transform operations: When concurrent operations are received, transform them against each other to maintain a consistent document state across all clients.
  3. Maintain document state: Accurately reflect the document's content after applying a sequence of transformed operations.

Key Requirements:

  • Document Representation: The document can be represented as a simple string.
  • Operation Types: Support two basic operation types:
    • Insert(position: number, text: string): Inserts text at position.
    • Delete(position: number, length: number): Deletes length characters starting from position.
  • Transformation Logic: Implement the core OT transformation functions. Specifically, you'll need to implement the logic to transform an incoming operation against a previously applied operation, and vice-versa.
  • State Management: The React component should manage the current document state and the history of operations.
  • Real-time Simulation: For this challenge, you will simulate real-time by manually applying sequences of operations. In a true real-time scenario, these operations would come from a network.

Expected Behavior:

When multiple operations are applied concurrently, the OT algorithm ensures that the final document state is consistent regardless of the order in which the operations are processed by a specific client. For example, if User A inserts "hello" at position 5 and User B inserts "world" at position 5, the final document should reflect both insertions in a predictable way.

Edge Cases:

  • Operations at the beginning and end of the document.
  • Operations that delete characters that were just inserted.
  • Concurrent insertions at the same position.
  • Concurrent deletions of overlapping ranges.

Examples

Example 1:

  • Initial Document: "abc"

  • Operation 1 (User A): Insert(position: 1, text: "X")

  • Operation 2 (User B): Insert(position: 2, text: "Y")

  • Scenario: If Operation 1 is applied first, then Operation 2 is transformed against Operation 1 and applied.

    • Apply Op 1: "aXbc"
    • Transform Op 2 against Op 1: Op 2 becomes Insert(position: 3, text: "Y") because Op 1 inserted at position 1, shifting subsequent positions.
    • Apply transformed Op 2: "aXYbc"

  • Scenario: If Operation 2 is applied first, then Operation 1 is transformed against Operation 2 and applied.

    • Apply Op 2: "abYc"
    • Transform Op 1 against Op 2: Op 1 becomes Insert(position: 1, text: "X") because Op 2 inserted at position 2, which is after Op 1's intended position and doesn't affect it.
    • Apply transformed Op 1: "aXbYc"

  • Explanation: Both scenarios result in the same final document state "aXYbc" due to the correct transformation logic.

Example 2:

  • Initial Document: "abcdef"

  • Operation 1 (User A): Delete(position: 2, length: 2) (deletes "cd")

  • Operation 2 (User B): Insert(position: 3, text: "XYZ")

  • Scenario: Op 1 applied first, then Op 2 transformed against Op 1.

    • Apply Op 1: "abef"
    • Transform Op 2 against Op 1: Op 2 was intended to insert at position 3 in "abcdef". Op 1 deleted 2 characters starting at position 2. So, the new position for Op 2 is 3 - 2 = 1.
    • Apply transformed Op 2: Insert(position: 1, text: "XYZ") to "abef" results in "aXYZbef"

  • Scenario: Op 2 applied first, then Op 1 transformed against Op 2.

    • Apply Op 2: "abcXYZdef"
    • Transform Op 1 against Op 2: Op 1 was intended to delete from position 2. Op 2 inserted 3 characters at position 3. Since Op 1's position (2) is before Op 2's position (3), Op 1's position is unaffected. The length of the deletion also remains the same.
    • Apply transformed Op 1: Delete(position: 2, length: 2) from "abcXYZdef" results in "abXYZdef"

  • Explanation: The final state is "abXYZdef". Note that the position of the deletion in the second scenario is adjusted by the insertion in the first scenario. The core transformation functions need to handle this carefully.

Example 3: Concurrent Deletions

  • Initial Document: "abcdefg"

  • Operation 1 (User A): Delete(position: 2, length: 3) (deletes "cde")

  • Operation 2 (User B): Delete(position: 3, length: 3) (deletes "def")

  • Scenario: Op 1 applied first, then Op 2 transformed against Op 1.

    • Apply Op 1: "abfg"

    • Transform Op 2 against Op 1: Op 2 intended to delete from position 3 in "abcdefg". Op 1 deleted 3 chars from pos 2. So Op 2's target position is now 3 - 3 = 0. The length of deletion needs to be checked against remaining characters. Op 2 intended to delete 3 chars. After Op 1, the document is "abfg". Deleting 3 chars from position 0 would try to delete "abf".

    • Let's re-evaluate the transformation for deletions. If Op1 deletes [p1, p1+l1) and Op2 targets [p2, p2+l2):

      • If Op2 starts after Op1 ends (p2 >= p1 + l1), Op2's position is unchanged.
      • If Op2 starts before Op1 ends (p2 < p1 + l1), Op2's position is shifted back by l1 if p2 < p1. If p1 <= p2 < p1 + l1, the part of Op2 that overlaps with Op1 is effectively removed.
      • The length of Op2 might also need to be reduced if it overlaps with Op1.

    • Applying this refined logic: Op 1 Delete(2, 3) on "abcdefg" -> "abfg".

    • Op 2 Delete(3, 3) targets [3, 6) in "abcdefg". Op 1 targets [2, 5).

    • p1=2, l1=3, p2=3, l2=3.

    • p2 (3) is less than p1 + l1 (5). p1 (2) is less than or equal to p2 (3).

    • The overlap is from position 3 up to the minimum of p1+l1 (5) and p2+l2 (6), which is position 5. The overlap length is min(p1+l1, p2+l2) - max(p1, p2) = min(5, 6) - max(2, 3) = 5 - 3 = 2.

    • The effective start of Op2 becomes p2 - p1 = 3 - 2 = 1 relative to the document after Op1.

Constraints

  • The document string length will not exceed 10,000 characters.
  • The number of operations in a sequence will not exceed 1,000.
  • Operation positions will always be valid within the current document bounds at the time of application (or transformed position).
  • Operation lengths for deletions will be non-negative.
  • Performance is important; the transformation logic should be reasonably efficient, aiming for O(N) or better for transforming a single operation against another, where N is the document length.

Notes

  • This challenge is about implementing the core transformation logic, not necessarily a full-blown real-time communication system. You can simulate the "real-time" aspect by creating sequences of operations and applying them.
  • Consider the (o1, o2) transformation function, which transforms o2 against o1. You will also need (o2, o1) or a symmetric transformation logic.
  • Think carefully about how insertions shift positions and how deletions affect both positions and lengths.
  • There are different OT algorithms (e.g., Live, Logoot). For this challenge, focus on a widely understood approach where operations are transformed against each other.
  • When dealing with concurrent operations, one operation is typically considered "older" or "canonical" for transformation purposes. In your React component, you might have a primary document state and a queue of incoming operations. Each incoming operation needs to be transformed against all operations already committed to the primary state.
  • You will likely need helper functions to manage the document string (inserting/deleting characters) and to apply operations to the string.
Loading editor...
typescript

The effective length of Op2 becomes l2 - overlap_length = 3 - 2 = 1.

  • Transformed Op 2: Delete(position: 1, length: 1) on "abfg".

  • Applying transformed Op 2: "afg".

  • Scenario: Op 2 applied first, then Op 1 transformed against Op 2.

    • Apply Op 2: Delete(3, 3) on "abcdefg" -> "abcg".
    • Transform Op 1 against Op 2: Op 1 Delete(2, 3) targets [2, 5) in "abcdefg". Op 2 targets [3, 6).
    • p1=2, l1=3, p2=3, l2=3.
    • p1 (2) is less than p2 (3). Op 1's position is unchanged.
    • The overlap length is min(p1+l1, p2+l2) - max(p1, p2) = min(5, 6) - max(2, 3) = 5 - 3 = 2.
    • The effective length of Op 1 becomes l1 - overlap_length = 3 - 2 = 1.
    • Transformed Op 1: Delete(position: 2, length: 1) on "abcg".
    • Applying transformed Op 1: "abg".

  • Explanation: The final state depends on the order of application and the correct transformation logic. For Delete operations, the final state should be consistent. In this case, the states are "afg" and "abg". This highlights a crucial aspect of OT: the transformation functions must be carefully designed to ensure convergence. A common convention is to ensure that operations originating from the same time-stamp (or implicitly by their order of creation) are treated consistently. For this problem, we'll assume operations are processed sequentially and focus on the transformation logic between two operations. The goal is to derive one correct transformation logic that leads to a consistent final state.