Q. How does the balancing factor of an AVL tree node get calculated?
A.
Height of left subtree - height of right subtree
B.
Height of right subtree - height of left subtree
C.
Number of nodes in left subtree - number of nodes in right subtree
D.
Number of nodes in right subtree - number of nodes in left subtree
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Solution
The balancing factor of an AVL tree node is calculated as the height of the left subtree minus the height of the right subtree.
Correct Answer:
A
— Height of left subtree - height of right subtree
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Q. In which scenario would an AVL tree be preferred over a Red-Black tree?
A.
When insertions and deletions are more frequent than searches.
B.
When search operations are more frequent than insertions and deletions.
C.
When memory usage is a concern.
D.
When the dataset is small.
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Solution
AVL trees are preferred when search operations are more frequent than insertions and deletions because they provide faster search times due to stricter balancing.
Correct Answer:
B
— When search operations are more frequent than insertions and deletions.
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Q. What is the main advantage of using an AVL tree over a Red-Black tree?
A.
AVL trees are faster for insertion operations.
B.
AVL trees maintain a stricter balance than Red-Black trees.
C.
Red-Black trees require less memory.
D.
AVL trees are easier to implement.
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Solution
AVL trees maintain a stricter balance than Red-Black trees, which can lead to faster lookups.
Correct Answer:
B
— AVL trees maintain a stricter balance than Red-Black trees.
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Q. What is the primary application of AVL trees?
A.
Implementing priority queues.
B.
Maintaining sorted data with frequent insertions and deletions.
C.
Graph traversal.
D.
Dynamic programming.
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Solution
AVL trees are primarily used for maintaining sorted data with frequent insertions and deletions due to their balanced nature.
Correct Answer:
B
— Maintaining sorted data with frequent insertions and deletions.
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Q. What is the worst-case time complexity for insertion in a Red-Black tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
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Solution
The worst-case time complexity for insertion in a Red-Black tree is O(log n).
Correct Answer:
B
— O(log n)
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Q. Which of the following scenarios would benefit from using a Red-Black tree?
A.
When frequent insertions and deletions are expected.
B.
When the dataset is static and does not change.
C.
When searching is the only operation performed.
D.
When memory usage is a critical constraint.
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Solution
Red-Black trees are particularly beneficial in scenarios with frequent insertions and deletions due to their ability to maintain balance efficiently.
Correct Answer:
A
— When frequent insertions and deletions are expected.
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