Binary Trees Quiz Solutions
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What is the height of a binary tree that contains only a single root node?
- A) 0
- B) 1
- C) 2
- D) It depends entirely on the tree implementation
Answer: B) 1
Explanation: By standard node-counting convention, a binary tree containing exactly one node has a height of 1. (Note: If counting edges instead, it would be 0, but standard educational frameworks default to node counts).
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Which fundamental depth-first traversal method processes a binary tree in the exact sequence: Left Subtree, Root Node, Right Subtree?
- A) Pre-order traversal
- B) In-order traversal
- C) Post-order traversal
- D) Level-order traversal
Answer: B) In-order traversal
Explanation: In-order traversal strictly follows the Left-Root-Right pattern recursively. When executed on a binary search tree, this traversal returns elements in sorted order.
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In a traditional binary tree setup, what is the maximum possible number of nodes that can exist specifically at depth 'd'?
- A) 2^d
- B) 2^(d+1) - 1
- C) 2d
- D) d^2
Answer: A) 2^d
Explanation: Since every node in a binary tree can split into at most 2 children, the maximum node limit doubles with each level, scaling exactly as 2^d (assuming the root sits at depth 0).
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What is the average-case time complexity of looking up a unique key within a perfectly balanced Binary Search Tree (BST)?
- A) O(n)
- B) O(log n)
- C) O(n log n)
- D) O(1)
Answer: B) O(log n)
Explanation: A balanced BST splits the search space in half with every node comparison. This makes the search operational length proportional to the height of the tree, which is O(log n).
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Which structural rule must a binary tree satisfy to qualify as a valid Binary Search Tree?
- A) The left subtree of a node contains only keys lesser than the node's key.
- B) The right subtree of a node contains only keys greater than the node's key.
- C) Both A and B are true.
- D) None of the above rules apply.
Answer: C) Both A and B are true.
Explanation: To maintain the binary search variant, every single node must act as a boundary: all left elements must be strictly smaller than it, and all right elements must be strictly larger.
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Which of the following definitions precisely describes a 'Complete Binary Tree'?
- A) Every level is completely filled except possibly the last level, which is filled from left to right.
- B) All leaf nodes are forced to sit on the exact same depth layer.
- C) Every internal node is strictly forced to have exactly two children.
- D) The tree is fully skewed down one single child branch line.
Answer: A) Every level is completely filled except possibly the last level, which is filled from left to right.
Explanation: A complete binary tree keeps structural paths densely packed. Every single level is entirely filled, and the bottom-most level populates positions progressively from left to right without skipping spaces.
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What is the absolute maximum possible depth/height of an unconstrained binary tree structured with exactly 'n' nodes?
- A) n
- B) log n
- C) n / 2
- D) n - 1
Answer: A) n
Explanation: In a worst-case scenario where each node contains only one child, the tree stretches out into a single linear sequence. The depth matches the count of nodes, resulting in a height of n.
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Which implementation architectures can be used to determine the Lowest Common Ancestor (LCA) of two target nodes within a binary tree?
- A) A purely recursive post-order exploration stack
- B) An iterative parent-mapping pointer tracker using hash structures
- C) Both A and B
- D) None of the above methods are valid
Answer: C) Both A and B
Explanation: LCA problems can be handled recursively by bubbled matches from sub-branches, or iteratively by mapping out parent nodes via a look-up map and finding where their paths cross.
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Which specific traversal path strategy yields the contents of a valid Binary Search Tree in strict descending order?
- A) Standard In-order traversal
- B) Pre-order structural traversal
- C) Post-order cleanup traversal
- D) Reverse In-order traversal
Answer: D) Reverse In-order traversal
Explanation: While a standard in-order traversal (Left, Root, Right) yields elements in ascending order, reversing that approach to (Right, Root, Left) outputs the largest elements first, delivering a perfect descending list.
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What is the worst-case time complexity encountered when attempting to insert a new node into an unbalanced Binary Search Tree?
- A) O(log n)
- B) O(n)
- C) O(n log n)
- D) O(1)
Answer: B) O(n)
Explanation: If a BST gets heavily skewed into a linear chain, inserting an item that belongs at the very end requires iterating past every single existing element, leading to a worst-case time of O(n).