Graph Theory and Algorithms Concepts

Graph Theory and Algorithms Concepts

Assessment

Interactive Video

Science

8th Grade

Practice Problem

Hard

Created by

Wayground Resource Sheets

FREE Resource

8 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is an algorithm?

A type of computer hardware.

A specific set of steps used to perform a computation.

A high-level programming language.

A computer program that calculates exponents.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

The term "algorithm" is named after a Persian polymath who was one of the fathers of algebra. What was his name?

Ada Lovelace

Charles Babbage

Muhammad ibn Musa al-Khwarizmi

Tommy Flowers

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following tasks commonly performed by computers requires sorting?

Calculating the square root of a number.

Arranging emails by most recently sent.

Displaying a website.

Playing a video game.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

If a Selection Sort algorithm is used to sort an array of 'N' items, approximately how many steps will it take?

N steps

N * 2 steps

N^2 steps

Log(N) steps

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the computational complexity of Merge Sort?

O(n!)

O(n^2)

O(n log n)

O(log n)

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the three main components used to represent a graph in computer science?

Cities, roads, and travel time

Nodes, lines, and costs

Points, connections, and distances

Vertices, edges, and values

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does Dijkstra's Algorithm typically begin when searching for the shortest path?

By trying every possible path from the start to the end.

By randomly selecting a node and exploring its connections.

By starting at the node with the lowest known cost.

By exploring the path with the highest cost first.

8.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the improved computational complexity of Dijkstra's Algorithm?

O(n^2)

O(n!)

O(n log n + l)

O(log n)