Compare different types of data structures : Treaps

The video tutorial explains treaps, a data structure combining binary search trees and heaps. It covers treap properties, rotations, and operations like insertion and removal, implemented in Python. The tutorial emphasizes understanding rotations and balancing to maintain treap efficiency. Testing shows treaps maintain logarithmic height, ensuring efficient operations.

What is a treap?

• A type of graph

• A combination of a binary search tree and a heap

• A type of linked list

• A sorting algorithm

What is the average time complexity for operations in a treap?

• O(1)

• O(n^2)

• O(log n)

• O(n)

What is the significance of using random priorities in a treap?

• To increase the height of the tree

• To make the tree unbalanced

• To ensure the tree is balanced

• To decrease the height of the tree

What is the purpose of rotations in a treap?

• To delete nodes

• To sort the elements

• To maintain heap properties

• To increase the height of the tree

What happens during a right rotation in a treap?

• The parent node is deleted

• The right child becomes the parent

• The left child becomes the parent

• The tree is split into two

What information is stored in each node of a treap?

• Key, priority, and references to left and right children

• Only the key

• Only the priority

• Key and value

What is the role of the get_height function in a treap?

• To find the maximum key

• To delete a node

• To insert a new node

• To calculate the height of the tree

What does the rotate left function do in a treap?

• Moves the left child to the right

• Moves the right child to the left

• Swaps the left and right children

• Deletes the left child

How does the insertion function in a treap differ from a classical binary search tree?

• It does not allow duplicate keys

• It requires more code

• It does not use any rotations

• It uses rotations to maintain balance

Why is the remove function in a treap simpler than in a classical binary search tree?

• It requires more code

• It does not handle duplicate keys

• It does not remove nodes

• It uses rotations to remove nodes