Data Structures MCQs

Hash Table is commonly used for fast average-case dictionary operations.
Its design supports this task efficiently or naturally.

The defining property is that collisions must be handled when keys map to the same position.
The other statements describe different structures or concepts.

Hash Table fits because it supports fast average-case dictionary operations and collisions must be handled when keys map to the same position.
Both clues point to this choice.

Separate Chaining is a collision-resolution method storing multiple entries in each hash bucket.
This description distinguishes it from the other choices.

Separate Chaining is commonly used for hash tables with flexible load factors.
Its design supports this task efficiently or naturally.

The defining property is that each bucket commonly references a list or another secondary structure.
The other statements describe different structures or concepts.

Separate Chaining fits because it supports hash tables with flexible load factors and each bucket commonly references a list or another secondary structure.
Both clues point to this choice.

Fibonacci Heap fits because it supports algorithms with many decrease-key operations and it provides excellent amortized decrease-key performance.
Both clues point to this choice.

Hash Table is a structure that maps keys to array positions using a hash function.
This description distinguishes it from the other choices.

Binomial Heap is commonly used for priority queues requiring efficient meld operations.
Its design supports this task efficiently or naturally.

The defining property is that there is at most one binomial tree of each degree.
The other statements describe different structures or concepts.

Binomial Heap fits because it supports priority queues requiring efficient meld operations and there is at most one binomial tree of each degree.
Both clues point to this choice.