What metrics prove DFS Cycle Detection (Directed Graph) is healthy in prod?

Answers use simple, clear English.

Quick 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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