AI In Software Testing Notes

Overview

The "AI in Software Testing Complete Guide" is a practical handbook designed for QA, SDET, and API testers. It covers two main areas: using AI tools to enhance testing processes and testing AI-powered products directly. The guide explores how testers can leverage AI for tasks such as test design, automation, and analysis, helping them to test faster. Additionally, the PDF prepares testers to evaluate AI systems, including LLMs, RAG, and agents. Topics include prompt engineering, LLM evaluation, security, governance, and adoption strategies. It provides essential skills for modern QA engineers working with AI, ensuring they can both utilize AI for testing and effectively test AI systems themselves.

Table of contents

1. AI and Testing: The Big Picture
2. How LLMs Work: A Tester's Mental Model
3. Prompt Engineering for Testers
4. Ready-to-Use Prompt Library
5. AI for Test Design
6. AI for Test Automation
7. AI Across Other Types of Testing
8. AI in Defect Management and Test Analytics
9. Testing AI Systems: Concepts and Metrics
10. Testing LLM Apps, RAG and Agents
11. Risks, Ethics and Governance
12. The Tool Landscape and How to Choose
13. Adopting AI in Your Team
14. Skills and Career in the AI Era
15. Interview Questions and Answers
16. Cheat Sheet and Glossary

Who this resource is for

• QA Engineer

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