Practice Formal Algorithm Description - 26.1.7.2 | 26. Shortest Paths in Weighted Graphs | Design & Analysis of Algorithms - Vol 1
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Formal Algorithm Description

26.1.7.2 - Formal Algorithm Description

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is a weighted graph?

💡 Hint: Think about graphs with varying edge costs.

Question 2 Easy

What does Dijkstra's Algorithm do?

💡 Hint: Recall the fire spreading analogy.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary objective of Dijkstra's Algorithm?

To find the longest path
To find the shortest path from a single source
To connect all vertices

💡 Hint: Focus on the term 'shortest path'.

Question 2

True or False: Dijkstra's Algorithm can handle graphs with negative edge weights.

True
False

💡 Hint: Remember how weights work in the algorithm.

Get performance evaluation

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a graph with vertices A, B, C, and D, and edges with weights between them, find the shortest path from A to D using Dijkstra's algorithm.

💡 Hint: Don't forget to update the neighbors' costs after visiting a vertex.

Challenge 2 Hard

Explain why Dijkstra's algorithm fails with negatively weighted edges, and provide an example.

💡 Hint: Consider paths that could 'get shorter' after visiting them.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.