Modify a data structure : Linked List Wrap-Up

The video tutorial discusses the performance and practical applications of linked lists. It explains the time complexity of linked lists, highlighting their efficiency in adding and removing nodes. The tutorial also explores practical uses, such as in online gaming, and discusses the advantages of linked lists in memory management, especially in low-level languages. The video concludes with a brief introduction to the next topic, binary search trees.

What is the time complexity for adding or removing nodes at the head or tail of a linked list?

• O(n^2)

• O(n)

• O(1)

• O(log n)

Why is searching in a linked list considered to have linear time complexity?

• Because each node points to the previous node

• Because the list is stored in a contiguous block of memory

• Because linked lists are sorted by default

• Because you may need to traverse the entire list to find an element

In what scenario might you use a circular linked list?

• To store sorted data

• To implement a stack

• To manage player turns in an online game

• To create a queue

What is a key advantage of using linked lists in lower-level languages?

• They automatically sort data

• They allow data to be stored in non-contiguous memory locations

• They require less memory than arrays

• They are faster than arrays for all operations

How do linked lists help in efficient memory usage?

• By using less memory than other data structures

• By storing all data in a single memory block

• By allowing data to be spread across different memory areas

• By compressing data