Data Structures and Algorithms The Complete Masterclass - Adelson-Vekskii Landis (AVL) Trees versus Red Black Trees

What is a primary issue with unbalanced Binary Search Trees?

• They are not suitable for large datasets.

• They require more memory.

• They can lead to inefficient search operations.

• They are difficult to implement.

What is the purpose of the Visual Go tool?

• To create new algorithms.

• To debug programs.

• To compile code.

• To visualize and understand algorithms.

How do AVL trees maintain balance?

• By limiting the number of nodes.

• By rebalancing after every insertion or deletion.

• By using a fixed structure.

• By using a random node selection.

What happens when an AVL tree becomes unbalanced?

• It becomes a Red-Black Tree.

• It deletes some nodes.

• It stops accepting new nodes.

• It automatically restructures itself.

What is a unique feature of Red-Black Trees?

• They use color properties to maintain balance.

• They do not require balancing.

• They have a fixed height.

• They use only black nodes.

Why is it not recommended for beginners to implement Red-Black Trees immediately?

• They are not used in real-world applications.

• They are too simple.

• They require understanding of complex balancing techniques.

• They are outdated.

What is the main advantage of using AVL and Red-Black Trees over simple Binary Search Trees?

• They are easier to code.

• They use less memory.

• They are faster to implement.

• They provide self-balancing capabilities.