Balanced Trees: AVL and Red-Black Trees - Applications - Problem Set

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Q. How do AVL trees handle insertion that causes imbalance?
  • A. By performing a single rotation
  • B. By performing a double rotation
  • C. By ignoring the new node
  • D. By deleting the node causing imbalance
Q. What is the main advantage of using balanced trees like AVL and Red-Black Trees?
  • A. They use less memory
  • B. They guarantee O(log n) time complexity for all operations
  • C. They are easier to implement
  • D. They can store duplicate values
Q. Which of the following is true about Red-Black Trees?
  • A. They are always perfectly balanced
  • B. They can have a maximum height of 2 log n
  • C. They guarantee O(log n) time for all operations
  • D. They require more memory than AVL trees
Q. Which of the following is true about the performance of AVL trees?
  • A. Faster than Red-Black Trees for all operations
  • B. Slower than Red-Black Trees for all operations
  • C. Faster for search operations but slower for insertions
  • D. Slower for search operations but faster for insertions
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