How to Use GitHub Copilot

Introduction

GitHub Copilot has been a game-changer for developers looking to write code faster, with fewer errors, and a smoother workflow. It's an AI pair programmer that takes a lot of the heavy lifting out of coding, freeing up your time and energy to focus on the bigger picture. In this blog post, we'll dive into how to use GitHub Copilot effectively and explore how it can significantly improve your productivity as a developer.

But we'll also go one step further and look at what else AI can do for developers beyond GitHub Copilot's capabilities. Stick around until the end, where we'll explore how Fine can fill in the gaps.

Table of Contents

1. Introduction
2. What Can GitHub Copilot Do?
3. How GitHub Copilot Can Make You Faster
4. Practical Steps to Use GitHub Copilot
5. Why Does GitHub Copilot Hallucinate?
6. Best Practices for Using Copilot Safely
7. Limitations of GitHub Copilot
8. What Else Can AI Do for Developers?
9. Conclusion

What Can GitHub Copilot Do?

GitHub Copilot is designed to be your AI assistant, generating code suggestions based on the context of your work. Here are some of its standout features:

• Code Generation: Copilot can generate whole lines or even blocks of code, based on natural language comments or existing code context.

• Autocomplete Functionality: It helps autocomplete methods, variables, and even complex logic based on what it thinks you need next, making your coding process faster and less repetitive.

• Code Examples and Snippets: If you're dealing with a function or algorithm you're not familiar with, Copilot can provide examples to guide you.

• Multi-language Support: Copilot isn't limited to a specific language; it supports Python, JavaScript, TypeScript, Ruby, and many more.

How GitHub Copilot Can Make You Faster

• Speed Up Boilerplate Code: By generating repetitive boilerplate code, Copilot saves hours that developers often lose to monotonous tasks.

• Discover New APIs and Methods: It can introduce you to libraries or functions that you might not be familiar with, expanding your toolkit while you're working.

• Natural Language to Code: Simply typing what you want in plain English can lead Copilot to write the corresponding code for you. This saves time looking up syntax or fiddling with commands.

Practical Steps to Use GitHub Copilot

1. Install the Extension: First, install GitHub Copilot from the Visual Studio Code extensions marketplace.
2. Activate Copilot: Once installed, make sure to sign in with your GitHub account to activate Copilot.
3. Write Natural Language Comments: Start by writing comments like "// Create a function to calculate Fibonacci numbers". Copilot will suggest code based on your comments.
4. Accept or Modify Suggestions: Review Copilot's suggestions and either accept them, modify them, or ask for alternatives by pressing Tab to cycle through options.
5. Customize Settings: Go into Copilot's settings and tweak how often you receive suggestions, the types of suggestions, and more, to tailor the experience to your workflow.

Why Does GitHub Copilot Hallucinate?

GitHub Copilot can sometimes generate code that seems correct but actually contains logical flaws, outdated practices, or even completely incorrect information. This phenomenon is often referred to as AI "hallucination." These hallucinations occur because Copilot generates responses based on the vast datasets it was trained on, but it doesn't fully understand the context or correctness of the code. Instead, it predicts what comes next based on patterns it has seen before. Additionally, Copilot has limitations in understanding broader project-specific contexts, which can lead to suggestions that don't align with your particular use case. This is why reviewing and testing the code suggestions provided by Copilot is always necessary to avoid unintended errors or vulnerabilities.

Best Practices for Using Copilot Safely

To make the most of GitHub Copilot while ensuring your code remains secure and of high quality, consider these best practices:

• Always Review Generated Code: Never assume the generated code is flawless. Make sure to review it thoroughly to avoid introducing bugs or vulnerabilities into your project.
• Test All Suggestions: Just like any other code, make sure to test the suggestions provided by Copilot. This helps you catch any mistakes or unexpected behaviors early on.
• Avoid Sensitive Data Handling: Do not use Copilot for generating code that handles sensitive information, like authentication or encryption, as it may inadvertently introduce security risks.
• Understand the Code: Use Copilot as a guide, not a crutch. Always strive to understand the code being generated, so you can effectively modify and maintain it over time.

Limitations of GitHub Copilot

While Copilot is a powerful tool, it's important to recognize its limitations:

• Lack of Deep Context Awareness: Copilot generates suggestions based on the immediate context but lacks a deep understanding of your entire project. This means it might provide code that doesn't fit well with your broader application logic.
• Risk of Outdated Practices: The AI model was trained on a large dataset that includes both modern and outdated code. As a result, it can sometimes suggest practices that are no longer recommended.
• Potential Security Risks: Since Copilot generates code based on patterns it has seen, it may inadvertently include insecure coding practices. This makes it crucial for developers to have a good understanding of security best practices when using it.
• No Guarantee of Originality: The code Copilot suggests may resemble code from public repositories, potentially raising licensing concerns. Be mindful of this when using its suggestions in proprietary software.

What Else Can AI Do for Developers?

GitHub Copilot is amazing, but it's not the only player in the field of AI-driven development tools. If you want more than just code suggestions, let’s look at some other tasks that AI can automate for you, and this is where Fine comes into the picture.

• Help Getting Started: If you're not sure how to begin addressing a feature or an issue, or if you're not sure where in the codebase the relevant code is, just ask Fine. Within GitHub Issues or Linear, you can comment /guideme and Fine will break down the task for you.

• Answer Questions About Your Code: You can ask Fine questions about your code or different tasks you've been given to get quick answers. Using the power of the LLMs and the knowledge of your codebase, Fine will help you solve puzzles.

• Revisions to PRs in your browser: Need to make a small change to a PR? Fine allows you to comment /revise on the PR in GitHub followed by the change you'd like and the AI does it for you.

• Comprehensive Code Documentation: Fine automatically documents your code and changes, making it easier for your team to understand and maintain code for years to come.

• Automate AI workflows: Using Fine, you can set up AI to perform repeated tasks automatically - such as summarizing and reviewing all new PRs.

Conclusion

GitHub Copilot is an incredible AI assistant that can boost your efficiency by speeding up coding tasks, reducing repetition, and helping you learn on the go. But, if you're looking to level up your entire development process, from security to bug detection and comprehensive documentation, Fine has a lot to offer.

Ready to see how AI can transform the way you work beyond code suggestions? Sign up for Fine today and discover the difference.