Description

Software Testing with Generative AI.

Software Testing with Generative AI: Smarter Testing for Modern Development Teams

Discover how generative AI and large language models (LLMs) can transform your software testing workflow, helping you create better tests, automate repetitive tasks, and deliver higher-quality software in less time.

Book Overview

Modern software development demands faster releases without compromising quality. Software Testing with Generative AI demonstrates how AI-powered tools can enhance every stage of the testing process—from planning and automation to exploratory testing and data generation.

Rather than relying on hype, this practical guide focuses on proven strategies for integrating generative AI into real-world testing environments. You’ll learn how to identify opportunities where AI can improve efficiency, expand test coverage, and support better decision-making throughout the software development lifecycle.

The book introduces the fundamentals of working with large language models, prompt engineering, and AI-assisted workflows before moving into practical applications. You’ll explore how AI tools can help automate test creation, generate realistic test data, improve UI automation, assist with exploratory testing, and support test-driven development using modern coding assistants.

Advanced chapters cover building customized language models, implementing retrieval-augmented generation (RAG), and adapting AI systems with domain-specific knowledge to meet organizational requirements.

By the end of this guide, you’ll understand how to use generative AI responsibly and effectively to improve software quality, reduce manual effort, and build more efficient testing processes.

What You’ll Learn

• Identify opportunities to improve software testing with AI
• Increase test quality and expand testing coverage
• Build and enhance automated testing workflows using AI tools
• Generate realistic test data with large language models
• Improve exploratory testing through AI-assisted idea generation
• Design more testable software using AI-driven insights
• Apply prompt engineering techniques for better AI results
• Use AI coding assistants to support test-driven development
• Create customized LLMs tailored to business-specific testing needs
• Implement retrieval-augmented generation (RAG) for context-aware AI systems
• Fine-tune AI models using organizational knowledge and domain expertise
• Build AI-powered testing assistants for modern development teams

Who This Book Is For

This book is ideal for software developers, QA engineers, software testers, test automation engineers, quality assurance professionals, and engineering teams interested in integrating generative AI into their testing workflows.

Readers with a basic understanding of software development or testing will gain practical knowledge for applying AI tools to improve productivity and software quality.

Table of Contents

Part 1: Foundations of AI-Assisted Testing

1. Enhancing Testing with Large Language Models
2. Large Language Models and Prompt Engineering
3. Artificial Intelligence, Automation, and Software Testing

Part 2: Applying AI to Software Testing

4. AI-Assisted Testing for Developers
5. Test Planning with AI Support
6. Rapid Test Data Generation Using AI
7. Accelerating UI Automation with AI
8. Enhancing Exploratory Testing with Artificial Intelligence
9. AI Agents as Testing Assistants

Part 3: Advanced AI Techniques

10. Building Customized Large Language Models
11. Retrieval-Augmented Generation for Context-Aware AI
12. Fine-Tuning LLMs with Business Domain Knowledge

Appendices

• Setting Up and Using ChatGPT
• Getting Started with GitHub Copilot
• Exploratory Testing Notes