← Early-stage Startup Interview Insights
First, clarify the problem to ensure it's a directed acyclic graph and identify the desired output (e.g., a valid topological order or cycle detection). Then, choose between Kahn's algorithm (BFS-based) or DFS-based topological sort, explaining your choice based on the graph's characteristics and constraints. Finally, walk through your solution with a small example, analyze time and space complexity, and discuss edge cases.
Pro tip: In a startup, demonstrating awareness of real-world constraints (e.g., scalability, memory) and trade-offs between algorithms shows maturity beyond just coding. Mention how you'd handle large graphs or dynamic updates if relevant.
Ask questions to confirm the graph type (directed, acyclic), input format, and expected output (e.g., any valid order, lexicographically smallest, or cycle detection).
Decide between Kahn's algorithm (BFS) and DFS-based topological sort, justifying your choice based on factors like cycle detection, ease of implementation, or specific constraints.
Explain the steps of your chosen algorithm, including data structures (e.g., queue, stack, indegree array) and how you'll handle visited nodes.
Trace the algorithm on a small graph to demonstrate correctness and clarify any ambiguities.
State time and space complexity, and discuss edge cases like empty graph, disconnected components, or cycles.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.