GenAI For Tester
  • Introduction
  • Session 1: Introduction to Generative AI in Testing
    • 1. Overview of Generative AI
    • 2. Popular AI Models and Their Usage
    • 3. Setting Up AI Tools for Testing
    • 4. Prompt Engineering for Software Testing
      • Prompt Managerment
  • Session 2: AI-Assisted Test Case Generation
    • Exam #1: eCommerce Domain - Checkout Flow
    • Exam #2: Mobile App - User Login and Authentication
    • Exam #3: API Testing - User Registration Endpoint
  • Session 3: Advanced AI in Test Automation
    • 🐍 Python 3.12 Setup Guide
    • Chrome AI Asistant
    • Setup Github Copilot in VS Code
    • Playwright MCP Server
    • SQLite MCP to interact with your DB
    • Browser-use Browser AI Agent
    • Postman PostBot AI for API Testing
    • Self Healing Elements with AgentQL and Playwright
  • n8n flexible AI workflow automation for technical teams
    • Setup n8n with docker
  • Build small thing with LLM
    • Create chatbot with gemini model
    • Create R.A.G with germini
    • Create AI Agent tool for query DB
  • Get selenium locator with llm and java
  • Group 1
    • Setup Local DB
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  1. Session 1: Introduction to Generative AI in Testing

2. Popular AI Models and Their Usage

🔹 Types of AI Models for Testing

  • LLM-based models (e.g., GPT-4, LLaMA, Gemini, Claude)

  • Code-generation models (e.g., Copilot, Code Llama)

  • AI-powered automation tools (e.g., Playwright AI, TestRigor)

🔹 Comparing AI Models for Testing

Model
Provider
Best Use Case in Testing

GPT-4

OpenAI

Test case & test data generation

Gemini

Google

AI-powered exploratory testing

LLaMA

Meta

Open-source AI for custom testing needs

Copilot

GitHub

AI-assisted code completion & test automation

TestRigor

AI Tool

No-code AI-powered test automation

🔹 Strengths & Weaknesses of AI in Testing

✅ Strengths:

  • Speeds up test design and data generation

  • Enhances test coverage with AI-driven test cases

  • Supports exploratory and automated testing

❌ Weaknesses:

  • Hallucinations in generated test cases

  • Lack of real-world contextual awareness

  • Requires human review and refinement of AI-generated results

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Last updated 3 months ago