Min Stacks

Min Stacks

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

Created by

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The lecture covers the concept of a min stack, a data structure that supports standard stack operations like push, pop, and top, along with an additional operation to retrieve the minimum element in constant time. The instructor explains the basic stack operations and introduces the get min functionality, which allows for efficient retrieval of the minimum element. The lecture also discusses the design of a min stack using an auxiliary stack to keep track of minimum values, ensuring constant time complexity for all operations.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary function of the 'push' operation in a stack?

To sort the stack

To remove the top item

To view the top item

To add an item to the stack

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In a stack, what does the 'pop' operation do?

Removes the top item

Duplicates the top item

Removes the bottom item

Adds an item to the stack

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the result of the 'top' operation in a stack?

The bottom item

The middle item

The top item

The smallest item

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What additional functionality does a min stack provide?

It allows sorting of elements

It retrieves the minimum element efficiently

It duplicates the stack

It reverses the stack

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does the 'get min' operation work in a min stack?

It retrieves the maximum element

It retrieves the last element

It retrieves the minimum element

It retrieves the middle element

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main challenge addressed by the min stack?

Reversing the stack

Finding the maximum element

Sorting the stack

Maintaining the minimum element efficiently

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the time complexity goal for retrieving the minimum element in a min stack?

O(n)

O(log n)

O(1)

O(n^2)

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