DFS Cycle Detection (Directed Graph)

Design a small subsystem that relies on DFS Cycle Detection (Directed Graph). Outline components, data flow, failure modes, and metrics.

Answers use simple, clear English.

Quick interview answer

Use DFS Cycle Detection (Directed Graph) as the core idea. Example shape: Build pipeline: detect circular module imports before CI runs..

Detailed answer

Use DFS Cycle Detection (Directed Graph) as the core idea. Example shape: Build pipeline: detect circular module imports before CI runs.. Watch for: Recursive DFS risks stack overflow on huge graphs; use iterative + explicit stack.. Measure success via latency/error/saturation. Core: Three-color DFS: white=unvisited, gray=in current stack, black=done. Back edge to gray node ⇒ cycle. Works for dependency graphs and course prerequisites. Real-time example: Build pipeline: detect circular module imports before CI runs. Pros: O(V+E); distinguishes directed vs undirected cycle logic. Cons: Recursive DFS risks stack overflow on huge graphs; use iterative + explicit stack. Common mistakes: Using two-color visited only (misses cross edges in undirected); forgetting disconnected components. Best practices: Loop all nodes as DFS roots; explain gray = active recursion path. Audience level: Fresher.

Full explanation

Three-color DFS: white=unvisited, gray=in current stack, black=done. Back edge to gray node ⇒ cycle. Works for dependency graphs and course prerequisites.

Real example & use case

Build pipeline: detect circular module imports before CI runs.

Pros & cons

Pros: O(V+E); distinguishes directed vs undirected cycle logic. Cons: Recursive DFS risks stack overflow on huge graphs; use iterative + explicit stack.

Common mistakes

Using two-color visited only (misses cross edges in undirected); forgetting disconnected components.