Data Structures and Algorithms The Complete Masterclass - Array - Common Operations – Part 2

The video tutorial covers the complexities of basic array operations: searching, copying, and insertion. It explains how these operations are performed, their time complexities, and the challenges they present, especially in terms of memory usage. The tutorial also introduces dynamic arrays, highlighting their advantages over static arrays, particularly in languages like Python and JavaScript.

What is the time complexity of searching for an element in an array?

• O(1)

• O(N)

• O(N^2)

• O(log N)

Why is copying an entire array considered inefficient?

• It can only be done in constant time.

• It requires additional memory and time.

• It does not require traversal of elements.

• It is only inefficient for arrays with less than 10 elements.

What is a major challenge when inserting an element in the middle of an array?

• Finding the correct index.

• Ensuring the array is sorted.

• Shifting elements and managing memory slots.

• Ensuring the array is not empty.

What happens if there is no available memory slot when inserting an element in an array?

• The system will compress the existing data.

• The array will be copied to a new location with extra space.

• The system will automatically delete other data.

• The insertion will fail.

What is the time complexity of inserting an element in an array?

• O(1)

• O(N)

• O(N^2)

• O(log N)

What is a key advantage of dynamic arrays over static arrays?

• They automatically resize as needed.

• They are only available in Python.

• They have a fixed size.

• They do not require memory allocation.

Which programming languages commonly use dynamic arrays?

• Python and JavaScript

• C and C++

• Ruby and PHP

• Java and C#