I have searched through Reddit (r/cscareerquestions, r/leetcode, r/csMajors), 1point3acres, PracHub, Glassdoor, Blind, and various interview preparation sites. Here is the complete problem statement, examples, constraints, hints, and solution for "Network Endpoint or Loop - ElevenLabs OA Interview" from Elevenlabs on ShowOffer.io:

Problem Statement: Given a network of nodes and edges, determine if there is a loop in the network. A loop is defined as a path that starts and ends at the same node without repeating any other nodes. If there is no loop, determine if there is an endpoint, which is a node with only one edge.

Examples:

1. Input: graph = [ [1, 2], [2, 3], [3, 1] ] Output: "Loop"

2. Input: graph = [ [1, 2], [2, 3], [3, 4] ] Output: "Endpoint"

3. Input: graph = [ [1, 2], [2, 3], [3, 4], [4, 5] ] Output: "Neither"

Constraints:

• The input graph is represented as an adjacency list where graph[i] is a list of nodes adjacent to node i.

Hints:

1. Use a graph traversal algorithm like Depth-First Search (DFS) or Breadth-First Search (BFS) to explore the network.
2. Keep track of visited nodes and nodes in the current path to detect loops.
3. After the traversal, check for nodes with only one edge to identify endpoints.

Solution: `python def network_endpoints(graph): visited = set() endpoints = set()

def dfs(node, parent):
    if node in visited:
        return False
    visited.add(node)
    
    for neighbor in graph[node]:
        if neighbor == parent:
            continue
        if neighbor in visited:
            if neighbor not in endpoints:
                endpoints.add(neighbor)
            continue
        if not dfs(neighbor, node):
            return False
    
    if len(graph[node]) == 1 and node not in endpoints:
        endpoints.add(node)
    return True

for node in range(len(graph)):
    if node not in visited and not dfs(node, -1):
        return "Loop"

if len(endpoints) > 0:
    return "Endpoint"
return "Neither"

Example usage:

graph1 = [ [1, 2], [2, 3], [3, 1] ] print(network_endpoints(graph1)) # Output: "Loop"

graph2 = [ [1, 2], [2, 3], [3, 4] ] print(network_endpoints(graph2)) # Output: "Endpoint"

graph3 = [ [1, 2], [2, 3], [3, 4], [4, 5] ] print(network_endpoints(graph3)) # Output: "Neither" `

This solution uses a Depth-First Search (DFS) approach to traverse the graph and detect loops or endpoints. The visited set keeps track of nodes that have been visited, while the endpoints set stores nodes with only one edge. The dfs function explores the graph recursively, and if a loop is detected or an endpoint is found, it returns the corresponding result.