Implement a Generic Graph Structure

To implement a generic graph structure suitable for high-scale systems, I would first define the data model. I'll use a HashMap where the key represents the vertex ID and the value is a List of neighboring vertex IDs. This ensures O(1) access for vertex lookups and efficient iteration over neighbors. For the generic aspect, I'd use a type parameter T to allow any comparable object as a node identifier. When adding a vertex, I simply check if it exists; if not, I initialize an empty list for it. Adding an edge involves retrieving the source list and appending the destination. If the graph is undirected, I must also append the source to the destination's list to maintain symmetry. For connectivity checking, a Breadth-First Search is ideal. I would start from the source node, enqueue it, and maintain a visited set to prevent cycles. As I dequeue nodes, I explore their neighbors until I find the target or exhaust all reachable nodes. This approach guarantees O(V + E) time complexity. In a real-world scenario like Stripe's payment routing, this structure efficiently models transaction flows. I would also ensure thread safety if used concurrently, perhaps by using synchronized blocks or concurrent collections, as reliability is paramount in financial infrastructure. Finally, I'd validate inputs to reject nulls or invalid connections before processing.