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Undecidable Problems

David Foster

David Foster

6 min read

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Study Guide Overview

This study guide covers decidability in computer science, focusing on the difference between decidable and undecidable problems. It explains the halting problem as a key example of an undecidable problem and explores the implications for the limits of computation. The guide also includes practice questions covering these concepts.

AP Computer Science Principles: Decidability - Your Last-Minute Guide

Hey there, future AP CSP superstar! Let's get you prepped and confident for your exam. We're diving into a tricky but crucial topic: decidability. Don't worry; we'll make it crystal clear.

What is Decidability? πŸ€”

At its heart, decidability is about whether we can write algorithms to solve problems. It's all about those yes/no questions!

Decidable Problems

  • Definition: A decidable problem is a decision problem (a problem with a yes/no answer) for which an algorithm can be written to produce a correct output for all possible inputs.
  • Think of it like this: If you can write a program that always gives the right answer, every single time, then you're dealing with a decidable problem.

Undecidable Problems

  • Definition: An undecidable problem is a decision problem for which no algorithm can be written that will always produce a correct yes or no answer.
  • Key Point: An undecidable problem might be solvable in some specific cases, but there's no single algorithm that works for every case. πŸ’‘
  • Analogy: Imagine trying to build a single key that opens every door in the world. It just can't be done! Some doors, maybe, but not all. That's like an undecidable problem.

Exam Tip

Remember, decidable problems have algorithms that always work, while undecidable problems don't. This distinction is crucial for the exam.


The Halting Problem: The Undecidable King πŸ‘‘

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Question 1 of 9

πŸŽ‰ A problem is considered decidable if:

It can be solved quickly by a computer

It has a yes/no answer and a guaranteed algorithm

It uses complex heuristics to find a solution

It is impossible to solve