Practice Intractability and Provably Hard Problems - 1.5.6 | 1. Welcome to the NPTEL MOOC on Design and Analysis of Algorithms | Design & Analysis of Algorithms - Vol 1
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1.5.6 - Intractability and Provably Hard Problems

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define intractability in your own words.

💡 Hint: Think about algorithm efficiency.

Question 2

Easy

What class of problems do we group NP-complete problems into?

💡 Hint: Reflect on problem classifications.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What defines an intractable problem?

  • A problem with a known efficient solution
  • A problem without an efficient known solution
  • A trivial problem

💡 Hint: Think about algorithm classifications.

Question 2

True or False: All NP-complete problems can be solved in polynomial time.

  • True
  • False

💡 Hint: Reflect on what makes a problem hard.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a new algorithm to solve a known NP-complete problem. Discuss the implications if your algorithm runs in polynomial time.

💡 Hint: Reflect on the importance of P vs NP.

Question 2

Discuss the consequences for practical applications if intractable problems could suddenly be solved efficiently.

💡 Hint: Consider how industries rely on current computational limits.

Challenge and get performance evaluation