Arctiq Copilot Learning Trail

Welcome to the Arctiq Copilot Learning Trail! This repository contains labs and code examples that can be used to gain a practical familiarity with using GitHub Copilot. The goal of this learning path is to give relatable examples and practical advice on how to get started using and getting real value out of GitHub Copilot.

Path Structure

This learning path includes several lab sections that cover the following topics:

Lab 1: About Copilot and how to start using it Lab 2: Using Copilot to extend existing application code Lab 3: Documentation, Explanation, and Refactoring Lab 4: Unit Testing and increasing Code Coverage Lab 5: Troubleshooting and debugging with Copilot

Lab Outlines

Lab 1: About Copilot and how to start using it

This lab will cover the brief history of Generative AI and how GitHub Copilot fits in.

Topics:

• What is Generative AI?
• How does Copilot fit in?
• Copilot is an API that can be used by various IDEs
• more?

Lab 2: Using Copilot to extend existing application code

This lab introduces the class to setting up Copilot in their chosen IDE and should cover the common examples of:

• VSCode
• IntelliJ IDEA
• Eclipse
• JetBrains WebStorm

There could be a brief section to explain the different capabilities of the Copilot agents across the IDEs.

Additionally, this lab will introduce the class to the example project and leap into extending a feature of the application that isn't quite complete. Attention should be paid to inline code-completion and when copilot chat is a better component to use.

Lab 3: Documentation, Explanation, and Refactoring

This lab will cover the aspects of generating documentation for methods and classes, getting an explanation of obfuscated/complicated code, and approaching refactoring of code using complexity scores as the guide to success.

This should include coverage of how to include additional project resources in the scope of the request using the various interfaces.

This lab will also include the important discussion on prompt engineering and how tuning how you request help can achieve different results.

Lab 4: Unit Testing and Increasing Code Coverage

This lab covers how to identify current code coverage using copilot, how to use copilot to assist in developing good test cases, and validating the coverage when complete.

Lab 5: Troubleshooting and Debugging with Copilot

In this lab, the class will use copilot for more than just code review, extension, and analysis. We will look at interpreting error messages, debugging output, and cryptic messages in the console.