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How to Test a Time Machine

You're reading from   How to Test a Time Machine A practical guide to test architecture and automation

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Product type Paperback
Published in Mar 2023
Publisher Packt
ISBN-13 9781801817028
Length 384 pages
Edition 1st Edition
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Author (1):
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Noemí Ferrera Noemí Ferrera
Author Profile Icon Noemí Ferrera
Noemí Ferrera
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1 Getting Started – Understanding Where You Are and Where You Want to Go
2. Chapter 1: Introduction – Finding Your QA Level FREE CHAPTER 3. Chapter 2: The Secret Passages of the Test Pyramid – The Base of the Pyramid 4. Chapter 3: The Secret Passages of the Test Pyramid – the Middle of the Pyramid 5. Chapter 4: The Secret Passages of the Test Pyramid – the Top of the Pyramid 6. Part 2 Changing the Status – Tips for Better Quality
7. Chapter 5: Testing Automation Patterns 8. Chapter 6: Continuous Testing – CI/CD and Other DevOps Concepts You Should Know 9. Chapter 7: Mathematics and Algorithms in Testing 10. Part 3 Going to the Next Level – New Technologies and Inspiring Stories
11. Chapter 8: Artificial Intelligence is the New Intelligence 12. Chapter 9: Having Your Head up in the Clouds 13. Chapter 10: Traveling Across Realities 14. Chapter 11: How to Test a Time Machine (and Other Hard-to-Test Applications) 15. Chapter 12: Taking Your Testing to the Next Level 16. Index 17. Other Books You May Enjoy Appendix – Self-Assessment

Summary

In this chapter, we reviewed AI, a concept that is getting more and more popular across all computing areas as more powerful machines and new algorithms that use that power get developed.

We started this chapter by exploring the foundations of AI and why it's important to know about this. Then, we reviewed some general knowledge about technical concepts related to AI.

We also saw some AI tools that could be of use for testing and learning about types of AI apps and the specifics of each type when it comes to testing them.

We completed the analyzer that we reviewed in the previous chapter with machine learning and looked at the difference between the two systems and when you should opt for one or the other.

We also looked at some examples related to reinforcement learning, which could be useful for finding solutions in games and other applications.

Finally, we talked briefly about tools for AI and other projects that could be of interest.

In the next chapter...

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