Collaborative Real-time Editing with CRDTs in React

Imagine building a collaborative document editor, a shared whiteboard, or any application where multiple users need to modify the same piece of state simultaneously and see each other's changes in real-time, even with network latency and disconnections. This challenge focuses on implementing Conflict-free Replicated Data Types (CRDTs) to manage such shared state effectively in a React application. You will build a basic CRDT implementation to handle concurrent updates and ensure eventual consistency across different clients.

Problem Description

The goal is to create a React component that manages a shared state using a CRDT. This component should allow multiple instances (simulating different users or clients) to modify the state independently and then merge their changes. The CRDT should handle potential conflicts arising from concurrent edits in a deterministic way, ensuring that all replicas converge to the same state over time.

Key Requirements:

CRDT State Management: Implement a CRDT data structure (e.g., a simple counter or a list) that can be updated locally and merged with updates from other replicas.
React Integration: Create a React hook or a higher-order component that encapsulates the CRDT logic and makes it easy to use within React applications.
Replication and Merging: Simulate network communication by allowing different React component instances (each representing a replica) to exchange their local CRDT state updates and merge them.
Eventual Consistency: Demonstrate that despite concurrent, potentially conflicting updates, all replicas eventually converge to the same consistent state.

Expected Behavior:

Each "client" (React component instance) should maintain its own local CRDT state.
When a client updates its state, this update should be generated and stored locally.
Clients should be able to "send" their updates to other clients.
Upon receiving an update from another client, the receiving client should merge it into its local CRDT state.
After all updates have been exchanged and merged, all clients should have the same final state.

Edge Cases to Consider:

Concurrent Updates: Two or more clients updating the same part of the state at nearly the same time.
Network Latency/Disconnection: Updates might arrive out of order or be delayed. (For this challenge, we'll simulate this by controlling the order of merging).
Crashes/Restarts: While not explicitly tested in the examples, a robust CRDT should be able to recover from such events if state is persisted.

Examples

For simplicity, we will implement a CRDT Counter. Each client will have a counter that can be incremented.

Example 1: Sequential Updates

Assume we have three clients: Client A, Client B, Client C.

Initial State (All Clients): CRDT Counter = 0
Client A: Increments its counter. Local CRDT state becomes 1.
Client B: Increments its counter. Local CRDT state becomes 1.
Client C: Increments its counter. Local CRDT state becomes 1.

Now, let's simulate merging:

Client A receives B's update: Merges 1 into its state. CRDT Counter = max(current_local_value, received_value) = max(1, 1) = 1.
Client A receives C's update: Merges 1 into its state. CRDT Counter = max(1, 1) = 1.
Client B receives A's update: Merges 1 into its state. CRDT Counter = max(1, 1) = 1.
Client B receives C's update: Merges 1 into its state. CRDT Counter = max(1, 1) = 1.
Client C receives A's update: Merges 1 into its state. CRDT Counter = max(1, 1) = 1.
Client C receives B's update: Merges 1 into its state. CRDT Counter = max(1, 1) = 1.

Final State (All Clients): CRDT Counter = 1.

Example 2: Concurrent Updates and Merging

Assume we have two clients: Client A, Client B.

Initial State (All Clients): CRDT Counter = 0
Client A: Increments its counter. Local CRDT state becomes 1.
Client B: Increments its counter. Local CRDT state becomes 1.
Client A: Increments its counter again. Local CRDT state becomes 2.
Client B: Increments its counter again. Local CRDT state becomes 2.

Now, let's simulate merging. Client A has updates leading to a local state of 2. Client B has updates leading to a local state of 2.

Client A receives B's updates: Client B might have generated updates that incremented its counter twice, resulting in a value of 2. Client A merges this.
- If Client A merges B's state of 2, its local counter becomes max(2, 2) = 2.
Client B receives A's updates: Similarly, Client B merges A's state.
- If Client B merges A's state of 2, its local counter becomes max(2, 2) = 2.

Final State (All Clients): CRDT Counter = 2.

Example 3: Demonstrating Convergence with Multiple Increments

Assume three clients: Client A, Client B, Client C.

Initial State: CRDT Counter = 0
Client A: Increments 3 times. Local state = 3.
Client B: Increments 2 times. Local state = 2.
Client C: Increments 1 time. Local state = 1.

Now, let's simulate the full exchange and merging. We'll represent the "updates" as the final local state value each client would have if they operated independently.

Client A's updates (value 3) are sent to B and C.
- Client B merges A's state: max(2, 3) = 3.
- Client C merges A's state: max(1, 3) = 3.
Client B's updates (value 2) are sent to A and C.
- Client A merges B's state: max(3, 2) = 3.
- Client C merges B's state: max(3, 2) = 3. (Note: C's state is already 3 from A's update).
Client C's updates (value 1) are sent to A and B.
- Client A merges C's state: max(3, 1) = 3.
- Client B merges C's state: max(3, 1) = 3.

Final State (All Clients): CRDT Counter = 3.

Constraints

The CRDT implementation should be written in TypeScript.
The React integration should utilize functional components and hooks.
The challenge focuses on the logic of CRDTs, so complex network simulation is not required. Direct function calls or event emitters can be used to simulate message passing.
The CRDT should support at least one operation (e.g., increment for a counter, append for a list).
Performance is not a primary concern for this introductory challenge, but the implementation should be reasonably efficient.

Notes

This challenge uses a simplified "Grow-only Counter" as a concrete example of a CRDT. A grow-only counter is a simple CRDT where the state only ever increases and conflicts are resolved by taking the maximum value. More complex CRDTs exist for other data structures (e.g., lists, maps, sets) that handle additions, deletions, and modifications with more sophisticated conflict resolution strategies.

Consider how you will represent the CRDT state and how updates will be generated and applied. Think about how to isolate the CRDT logic from the React component to make it reusable. You might explore libraries that provide CRDT primitives, but the core task is to understand and implement the merging logic.