Understanding Algorithms and Design Techniques

Understanding Algorithms and Design Techniques

University

9 Qs

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Understanding Algorithms and Design Techniques

Understanding Algorithms and Design Techniques

Assessment

Quiz

Computers

University

Practice Problem

Hard

Created by

John Blesswin

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9 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What are algorithms

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What does the word Algorithm mean?

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3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the Divide and Conquer Approach?

It is a top-down approach.

It is a bottom-up approach.

It involves solving all possible small problems.

It is a method for global optimization.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the Greedy Technique used for?

To solve optimization problems.

To divide problems into subproblems.

To combine solutions of subproblems.

To perform depth-first search.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is Dynamic Programming?

A top-down approach.

A bottom-up approach.

A method for global optimization.

A technique for random number generation.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the Branch and Bound algorithm do?

Divides a subproblem into at least two new restricted subproblems.

Combines solutions of subproblems.

Uses random bits to influence computation.

Tries each possibility until the right one is found.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a Randomized Algorithm?

An algorithm that uses random bits.

An algorithm that guarantees optimal solutions.

An algorithm that solves problems recursively.

An algorithm that divides problems into subproblems.

8.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the Backtracking Algorithm do?

Tries each possibility until the right one is found.

Uses random numbers to make decisions.

Divides problems into subproblems.

Combines solutions of subproblems.

9.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is an example of a Randomized Algorithm?

Using a random number to choose a pivot in Quick Sort.

Dividing a problem into subproblems.

Combining solutions of subproblems.

Using a greedy method to solve optimization problems.