Practice Naive vs. Incremental Computation - 25.1.6 | 25. DAGs: Longest Paths | 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

Naive vs. Incremental Computation

25.1.6 - Naive vs. Incremental Computation

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 Directed Acyclic Graph (DAG)?

💡 Hint: Think about arrows and paths.

Question 2 Easy

What does topological sorting accomplish?

💡 Hint: Consider task dependencies.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What defines a Directed Acyclic Graph (DAG)?

Has cycles
No cycles
Is undirected

💡 Hint: Focus on the acyclic part.

Question 2

Topological sorting arranges vertices in what manner?

True
False

💡 Hint: Think about the prerequisite relationships.

Get performance evaluation

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a set of tasks with dependencies listed as pairs (A, B) meaning A must be done before B, design a DAG and determine the longest path.

💡 Hint: Map out tasks visually.

Challenge 2 Hard

You have a set of 10 courses with specified prerequisites. How would you use the longest path concept to determine the course load a student would have each semester?

💡 Hint: Using a graph drawing can help clarify dependencies.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.