All MCQs

Red-Black Tree fits because it supports implementing ordered maps and sets and its rules guarantee logarithmic height without strict AVL-style balance.
Both clues point to this choice.

The defining property is that its rules guarantee logarithmic height without strict AVL-style balance.
The other statements describe different structures or concepts.

Red-Black Tree is commonly used for implementing ordered maps and sets.
Its design supports this task efficiently or naturally.

Red-Black Tree is a self-balancing binary search tree that uses node colors and structural rules.
This description distinguishes it from the other choices.

AVL Tree fits because it supports search-intensive applications requiring predictable logarithmic height and each node's balance factor is typically -1, 0, or 1.
Both clues point to this choice.

The defining property is that each node's balance factor is typically -1, 0, or 1.
The other statements describe different structures or concepts.

AVL Tree is commonly used for search-intensive applications requiring predictable logarithmic height.
Its design supports this task efficiently or naturally.

AVL Tree is a self-balancing binary search tree with tightly controlled subtree heights.
This description distinguishes it from the other choices.

Binary Search Tree fits because it supports ordered searching and dynamic set operations and an inorder traversal produces keys in sorted order.
Both clues point to this choice.

The defining property is that an inorder traversal produces keys in sorted order.
The other statements describe different structures or concepts.

Binary Search Tree is commonly used for ordered searching and dynamic set operations.
Its design supports this task efficiently or naturally.

Binary Search Tree is a binary tree where left-subtree keys are smaller and right-subtree keys are larger under a chosen ordering.
This description distinguishes it from the other choices.