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Start by clarifying the problem constraints and edge cases, then present both Kahn's algorithm (BFS-based) and DFS-based topological sort. Explain the time and space complexity of each, and discuss how to detect cycles. Finally, walk through a small example to illustrate the chosen approach.
Pro tip: Mention that Kahn's algorithm naturally detects cycles by checking if the number of processed nodes equals n, while DFS uses a recursion stack to detect back edges. This shows you understand the trade-offs and can adapt to different scenarios.
Confirm input format, whether nodes are 0-indexed or 1-indexed, and if the graph is guaranteed to be a DAG. Discuss edge cases like empty graph, single node, and disconnected components.
Explain computing in-degrees, using a queue to process nodes with zero in-degree, and decrementing in-degrees of neighbors. If the result size is less than n, a cycle exists.
Describe performing DFS with three states (unvisited, visiting, visited) to detect cycles. Add nodes to the result in post-order, then reverse the result to get topological order.
State that both approaches run in O(V+E) time and O(V+E) space. Discuss that Kahn's is iterative and easier to reason about for cycle detection, while DFS can be more intuitive for some and uses recursion.
Choose a small graph (e.g., 4 nodes with edges 1->2, 1->3, 2->4) and demonstrate the steps of the chosen algorithm, highlighting how cycle detection would work if an edge 4->1 were added.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.