About this video

• Video Title: GitHub Copilot tutorial with IntelliJ IDEA
• Channel: Craft Of Programming
• Speakers: Nilton (implied by closing statement)
• Duration: 53:31

Overview

This video provides a comprehensive tutorial on installing and utilizing GitHub Copilot within IntelliJ IDEA. It covers the plugin installation, handling keyboard shortcuts, integrating Copilot with the IDE, and then demonstrates its use through the development of a restaurant reservation system. The tutorial showcases Copilot's capabilities in generating code, implementing complex logic, writing unit tests, and improving documentation, while also discussing potential challenges and ways to refine its output.

Key takeaways

• GitHub Copilot Installation and Setup: The video details the process of installing the GitHub Copilot chat plugin in IntelliJ IDEA, including the need for a GitHub Copilot subscription and the login process within the IDE.
• IDE Integration and Shortcuts: It explains how to verify the plugin's status in IntelliJ IDEA and highlights potential conflicts with existing keyboard shortcuts, offering workarounds.
• Code Generation and Refinement: The tutorial demonstrates Copilot's ability to generate entire classes and implement interfaces based on provided constraints, as exemplified by the creation of a restaurant reservation system. It also shows how to refine generated code through iterative prompting.
• Unit Testing with Copilot: The video illustrates how Copilot can generate JUnit 5 parameterized tests to validate input parameters and ensure code robustness, including the process of fixing generated tests.
• Documentation Generation: It showcases Copilot's capability to generate JavaDocs for classes and methods, emphasizing that more specific prompts lead to more useful documentation.

You can utilize the AI agent by interacting with it through chat prompts within IntelliJ IDEA. As demonstrated in the video, you can ask it to:

• Generate code: Implement interfaces, create classes, or write specific methods based on your requirements.
• Write unit tests: Generate JUnit tests for your code, including parameterized tests for validation.
• Explain code: Understand the functionality of a method or class.
• Generate documentation: Create JavaDocs for your classes and methods.

The key to effectively using the AI agent is to provide clear, specific, and detailed prompts, including constraints and desired outcomes, to achieve the most accurate and useful results.