Generative AI ChatGPT and Google BARD for Software Engineers

سرفصل های دوره

Generative AI | Performance Test | API Testing | AI for Quality Engineering

1. Introduction

1. Introduction

2. Prompt Anatomy

3. Cascade Prompting

2. Google BARD - Orientation

1. Access to Google Bard

2. Important Links

3. Generate Alternative Answers

4. Change Tone and Lenght of Answer

5. Exporting Answers

6. Files and URL Manipulation

3. Google BARD - Explain Concept

1. Explain why do we need Quality Engineering

2. Explain a Framework - Selenium Webdriver

3. Compare 2 Testing Frameworks

4. Explain Concept - Test Pyramid

5. Explain Code - Java

6. Narrow down Results - Shifting Left

7. Explain Non Functional Testing

4. Google BARD - Practical - Create API CICD Test Framework

1. Understand Test Scope

2. Identify Test Scenarios and Data

3. Smoke Test from Command Line

4. Fix Comand Line Test

5. Create Java Project

6. Creating first Test Case

7. Resolve Dependencies

8. Execute First Test

9. Add Tests to Suite

10. Execute Java Test from Command Line

11. Create GitHub Repository

12. Setup Github Actions

13. Run Test on Azure Application

5. CHAT GPT - Accelerate Test Artifact Generation

1. Rapid Start your documentation

2. Aid in toolling and framework assesment

3. Using Generative AI to validate User Stories

4. Using ChatGPT for generating Test Cases from Acceptance Criteria

5. Automatically modify Tests

6. Generative AI for Test Data and Code

1. Generate Given When Then Scenarios

2. Generate Cucumber Feature Files

3. Generate Cucumber files with project context

4. Generate Automated Tests with Chat GPT

5. Generate Automated Tests with project context

6. Transform from Code to BDD - Cucumber

7. Adapting code with CHATGPT

8. Generate API call from Source Code

9. Using Chat GPT to help configure Postman

10. Seting up CLI Execution for Postman

11. Switch from one format to another Postman - Rest assured

12. Generate Test Data with AI

13. Generate SQL Queries

14. Generate large volumes of data

15. Setup Containers with AI - Docker

16. Using AI to add jobs in CICD pipeline

17. Using AI for setting up performance testing pipelines - GOOGLE LIGHTHOUSE

7. Complete Performance Project Creation with AI - CICD - Cloud Azure

1. Selecting the tool with AI

2. Create first performance Test Script

3. Add listener to Test Script

4. Adding Threads and Users

5. Generating Random Test Data

6. AI FAIL - Adding Results Summary

7. Adding Results Summary - The Solution

8. Running from Command Line

9. Creating Container Image

10. Setting up GITHUB Action

11. Run the Test in a Pipeline

12. Make Results Available

8. Aditional Material - Vertex AI -Google

1. Setting up the account

2. Create Project

3. Orientation in Vertex AI

4. Prompt Examples

5. First Prompt

6. Temperature of Model

7. Model Training - Manual

8. Model Training JSONL

9. Connecting through an API

9. Conclussion

1. Final Words

45,900 تومان

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تولید کننده: Udemy