- Construct test automation with the support of AI tools
- Formulate new ideas during exploratory testing using AI tools
- Use AI tools to aid the design process of new features
- Improve the testability of a context with the help of AI tools
- Maximize your output with prompt engineering
- Create custom LLMs for your business's specific needs Software Testing with Generative AI is full of hype-free advice for supporting your software testing with AI. In it, you'll find strategies from bestselling author Mark Winteringham to generate synthetic testing data, implement automation, and even augment and improve your test design with AI. Foreword by Nicola Martin. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology There's a simple rule in software testing: the more you test, the more you learn. And as any testing pro will tell you, good testing takes time. By integrating large language models (LLMs) and generative AI into your process, you can dramatically automate and enhance testing, improve quality and coverage, and deliver more meaningful results. About the book Software Testing with Generative AI shows you how AI can elevate every aspect of testing--automation, test data management, test scripting, exploratory testing, and more! Learn how to use AI coding tools like Copilot to guide test-driven development, get relevant feedback about your applications from ChatGPT, and use the OpenAI API to integrate AI into your data generation. You'll soon have higher-quality testing that takes up less of your time. What's inside - Improve test quality and coverage
- AI-powered test automation
- Build agents that act as testing assistants About the reader For developers, testers, and quality engineers. About the author Mark Winteringham is an experienced software tester who teaches many aspects of software testing. He is the author of Testing Web APIs. The technical editor on this book was Robert Walsh. Table of Contents Part 1
1 Enhancing testing with large language models
2 Large language models and prompt engineering
3 Artificial intelligence, automation, and testing
Part 2
4 AI-assisted testing for developers
5 Test planning with AI support
6 Rapid data creation using AI
7 Accelerating and improving UI automation using AI
8 Assisting exploratory testing with artificial intelligence
9 AI agents as testing assistants
Part 3
10 Introducing customized LLMs
11 Contextualizing prompts with retrieval-augmented generation
12 Fine-tuning LLMs with business domain knowledge
Appendix A Setting up and using ChatGPT
Appendix B Setting up and using GitHub Copilot
Appendix C Exploratory testing notes
- Construct test automation with the support of AI tools
- Formulate new ideas during exploratory testing using AI tools
- Use AI tools to aid the design process of new features
- Improve the testability of a context with the help of AI tools
- Maximize your output with prompt engineering
- Create custom LLMs for your business's specific needs Software Testing with Generative AI is full of hype-free advice for supporting your software testing with AI. In it, you'll find strategies from bestselling author Mark Winteringham to generate synthetic testing data, implement automation, and even augment and improve your test design with AI. Foreword by Nicola Martin. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology There's a simple rule in software testing: the more you test, the more you learn. And as any testing pro will tell you, good testing takes time. By integrating large language models (LLMs) and generative AI into your process, you can dramatically automate and enhance testing, improve quality and coverage, and deliver more meaningful results. About the book Software Testing with Generative AI shows you how AI can elevate every aspect of testing--automation, test data management, test scripting, exploratory testing, and more! Learn how to use AI coding tools like Copilot to guide test-driven development, get relevant feedback about your applications from ChatGPT, and use the OpenAI API to integrate AI into your data generation. You'll soon have higher-quality testing that takes up less of your time. What's inside - Improve test quality and coverage
- AI-powered test automation
- Build agents that act as testing assistants About the reader For developers, testers, and quality engineers. About the author Mark Winteringham is an experienced software tester who teaches many aspects of software testing. He is the author of Testing Web APIs. The technical editor on this book was Robert Walsh. Table of Contents Part 1
1 Enhancing testing with large language models
2 Large language models and prompt engineering
3 Artificial intelligence, automation, and testing
Part 2
4 AI-assisted testing for developers
5 Test planning with AI support
6 Rapid data creation using AI
7 Accelerating and improving UI automation using AI
8 Assisting exploratory testing with artificial intelligence
9 AI agents as testing assistants
Part 3
10 Introducing customized LLMs
11 Contextualizing prompts with retrieval-augmented generation
12 Fine-tuning LLMs with business domain knowledge
Appendix A Setting up and using ChatGPT
Appendix B Setting up and using GitHub Copilot
Appendix C Exploratory testing notes
Paperback
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