graph dfs traversal Pattern
Pattern hubs are for building transferable solving frames. Learn the recognition signals first, then drill state definition, update rules, and edge explanation until the pattern feels stable.
Pattern brief
Recognize first
Do you understand the importance of using a hash table to store visited nodes during graph traversal?
Solve rhythm
State the active state and invariant first, explain how each update preserves them, then pressure-test with counterexamples.
Most common miss
Not using a hash table to track cloned nodes, leading to cycles and duplicate clones.
Recognition signals
- Do you understand the importance of using a hash table to store visited nodes during graph traversal?
- Can you describe how to handle cycles when cloning a graph using DFS?
- Candidate identifies graph representation with adjacency lists.
Solve flow
- 1. Define the active state/window.
- 2. Update state while preserving invariants.
- 3. Validate with edge-heavy examples.
Common misses
- Not using a hash table to track cloned nodes, leading to cycles and duplicate clones.
- Failing to sort adjacency lists leading to incorrect lexical order.
- Forgetting to add the inverse edge 1/value, which breaks paths in DFS.
Recommended Ladder
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