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Consider two approaches to solve the Binary Tree Cameras problem: Approach 1: Brute force recursion exploring all camera placement combinations (O(2^n)) Approach 2: Greedy postorder traversal with explicit enum states (O(n)) When is Approach 1 preferable over Approach 2?

hard⚖️ Approach Comparison Q8 of Q15
Tree: Depth-First Search - Binary Tree Cameras
Consider two approaches to solve the Binary Tree Cameras problem: Approach 1: Brute force recursion exploring all camera placement combinations (O(2^n)) Approach 2: Greedy postorder traversal with explicit enum states (O(n)) When is Approach 1 preferable over Approach 2?
AWhen the tree is small and exhaustive search is feasible for exact enumeration
BWhen the tree is very large and performance is critical
CWhen the problem requires counting all possible minimal camera placements
DWhen cameras can cover nodes at arbitrary distances beyond parent and children
Step-by-Step Solution
Solution:

  1. Step 1: Analyze brute force approach

    Brute force explores all subsets, exponential time, feasible only for small trees.

  2. Step 2: Identify use case

    Exact enumeration or counting all minimal solutions requires brute force on small inputs.

  3. Step 3: Greedy approach is efficient but only finds one minimal solution

    Not suitable for counting or listing all solutions.

  4. Final Answer:

    Option A -> Option A

  5. Quick Check:

    Brute force preferred only for small trees and exhaustive enumeration [OK]
Quick Trick: Brute force for small trees and full enumeration [OK]
Common Mistakes:
MISTAKES
  • Assuming brute force is better for large trees or performance
Trap Explanation:
PITFALL
  • Candidates confuse brute force with efficiency rather than completeness.
Interviewer Note:
CONTEXT
  • Tests understanding of trade-offs between exhaustive and greedy approaches
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