Follow-up · depth 2
What metrics prove DFS Cycle Detection (Directed Graph) is healthy in prod?
What metrics prove DFS Cycle Detection (Directed Graph) is healthy in prod?
Answers use simple, clear English.
Audio N/AQuick interview answer
Prove DFS Cycle Detection (Directed Graph) is healthy with latency (p50/p95/p99), error/saturation rates, and queue/event-loop lag — not just CPU. Context: Mitigate first, then root-cause. Check symptoms against: Using two-color visited only (misses cross edges in undirected); forgetting disconnected components..
Detailed answer
Production health signals for DFS Cycle Detection (Directed Graph): • Latency: p50/p95/p99 of the critical path that uses DFS Cycle Detection (Directed Graph). • Errors: failure rate, timeouts, and retry storms. • Saturation: queue depth, event-loop delay, thread/pool utilization. • Business SLIs: request success and user-visible freshness where relevant. Trade-off lens: Pros: O(V+E); distinguishes directed vs undirected cycle logic. Cons: Recursive DFS risks stack overflow on huge graphs; use iterative + explicit stack. Explain thresholds + alerts, then how you triage. Parent context: Mitigate first, then root-cause. Check symptoms against: Using two-color visited only (misses cross edges in undirected); forgetting disconnected components..
Full explanation
Good answers name measurable signals and what “bad” looks like for DFS Cycle Detection (Directed Graph). Three-color DFS: white=unvisited, gray=in current stack, black=done. Back edge to gray node ⇒ cycle. Works for dependency graphs and course prerequisites.
Follow-up questions
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Parent context — DFS Cycle Detection (Directed Graph)
Mitigate first, then root-cause. Check symptoms against: Using two-color visited only (misses cross edges in undirected); forgetting disconnected components..
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