What is GitHub Copilot? The Benefits and Challenges

More Code, Less Hassle

• Less Googling, More Doing:

We've all been there, stuck in the endless loop of searching and cross-referencing code on Google or Stack Overflow. Copilot reduces that significantly by offering up solutions based on the vast sea of code it's been trained on. This means you spend less time searching and more time actually coding.

• Test Like a Pro:

Want to make sure your code is working right? Copilot can suggest test cases based on what you've written, making it a breeze to catch bugs before they cause problems.

• Help With Boilerplate Code:

Let's be honest, writing boilerplate code isn't the most exciting part of a project. Copilot can handle much of that for you, generating repetitive code patterns quickly so you can focus on the unique parts of your project that actually need your brainpower.

• Context-Aware Completions:

Copilot analyzes your code and project setup to suggest completions that match your coding style and project conventions.

• Increased Productivity:

By suggesting code snippets, Copilot can significantly speed up the coding process. It's like having an assistant who constantly suggests the next line of code, allowing developers to stay in the flow.

// Suppose you start typing a function to fetch user data:
async function getUserData(userId) {

  const response = await fetch(`https://api.example.com/users/${userId}`);

  // Copilot might suggest the next lines:

  const data = await response.json();

  return data;

}

This study is the right example to showcase that Copilot is helping devs improving their speed by upto 30%.

• Speak Many Languages:

Whether you're coding in Python, JavaScript, or any other popular language, Copilot has your back. It's pretty versatile and understands a bunch of languages and frameworks, which makes it a great tool no matter what tech stack you're using.

• Seamless Integration:

No need to switch between tools! Copilot works as an extension within your favorite editors like Neovim, JetBrains IDEs, Visual Studio, and Visual Studio Code. It integrates smoothly, keeping your workflow uninterrupted.

Let's See Copilot in Action

Imagine we're building a simple program in Python to figure out the area of a rectangle. Here's what we might start with:

def calculate_area(length, width):
  # What goes here?

Here, Copilot can take a look at what we've written and suggest the following code:

def calculate_area(length, width):
  """Calculates the area of a rectangle."""
  return length * width

Not only does it fill in the function, but it also adds a little comment to explain what the function does – double win!

But there’s always a con to everything

While Copilot is awesome, it's not perfect. Here's some of the shortcomings we feel Copilot has:

• Overreliance:

  Developers might become too dependent, potentially stifling their problem-solving skills.

• Accuracy Issues:

  Suggestions might not always be accurate or optimal, especially in complex or unique coding situations.

• Privacy Concerns:

  Since it's trained on public code, there's a risk of inadvertently suggesting code snippets that could violate privacy or security standards.

Keep in mind these best practices

• Double Check Everything: 

  Copilot's suggestions are just ideas, and sometimes those ideas might be wrong. It's important to review everything Copilot suggests before using it, just to make sure it makes sense.

• Give it Good Info: 

  Copilot works best when you give it clear instructions. If your code is messy or your comments don't explain what you're trying to do, Copilot might get confused and give you bad suggestions.

• Security Matters: 

  Be careful about using code that Copilot suggests, especially if you're not sure where it came from. There's a small chance it might have security problems or use code that belongs to someone else.

  
  

Some Use-cases of Copilot

1. Rapid Prototyping

When you're starting a new project, especially in a hackathon or a startup environment, speed is key. Copilot can quickly generate boilerplate code and suggest implementation options, allowing you to get a prototype up and running in no time.

// Let's say you need to set up an Express server in Node.js
app.get('/', (req, res) => {

    res.send('Hello World!');

});

Copilot can suggest the entire snippet as soon as you type app.get.

2. Learning New Languages or Frameworks

If you're diving into a new programming language or framework, Copilot can be incredibly helpful. It provides code snippets based on best practices, which not only helps you code but also teaches you the syntax and style of a new tech stack.

Start -> Type basic syntax -> Copilot suggests snippets -> Analyze and learn from suggestions -> Implement in your project -> Repeat

3. Debugging and Code Improvement

Stuck on a bug or not sure why your code isn’t efficient? Copilot can offer alternative ways to write the same function, which might give you a clue on how to fix or optimize your code.

# Original buggy code
for i in range(len(numbers)):

    print(i, numbers[i])

# Copilot suggestion for improvement

for index, number in enumerate(numbers):

    print(index, number)

Just start typing the class definition, and Copilot can help autocomplete much of the structure.

5. Writing Tests

Writing unit tests can be mundane. Copilot can suggest test cases based on your function signatures, speeding up the development of a robust test suite.

// Function to test
function add(a, b) {

    return a + b;

}

// Copilot suggested test

describe('add function', () => {

    test('adds two numbers', () => {

        expect(add(2, 3)).toBe(5);

    });

});

💡 Copilot understands the context and can suggest relevant test scenarios.

But it can not understand the user-flow journey of your app, and hence feels short when it comes to covering more test case scenarios’, and leaving no edge-cases untested. See HyperTest in action.

6. Documentation Writing

Even documentation can be streamlined. As you document your code, Copilot can suggest descriptions and parameter details based on the function signatures and common documentation patterns.

/**
 * Adds two numbers together.
 * @param {number} a - The first number.
 * @param {number} b - The second number.
 * @returns {number} The sum of a and b.
 */
function add(a, b) {

    return a + b;
}

These examples showcase how GitHub Copilot isn’t just about saving time—it’s about enhancing the way you work, learning as you go, and keeping the mundane parts of coding as painless as possible.

Some discussion-worthy features of Copilot

It’s features are what makes it extra-ordinary in the race of AI tools today. Let’s have a fair discussion around them also:

1. Context-Aware Code Suggestions

One of the standout features of GitHub Copilot is its ability to understand the context of the code you're working on. This isn't just about predicting the next word you might type but offering relevant code snippets based on the function you're implementing or the bug you're trying to fix.

// When you type a function to calculate age from birthdate:
function calculateAge(birthdate) {
    // Copilot automatically suggests the complete function:
    const today = new Date();
    const birthDate = new Date(birthdate);
    let age = today.getFullYear() - birthDate.getFullYear();
    const m = today.getMonth() - birthDate.getMonth();
    if (m < 0 || (m === 0 && today.getDate() < birthDate.getDate())) {
        age--;
    }
    return age;
}

2. Code in Multiple Languages

GitHub Copilot isn't limited to one or two languages; it supports a multitude of programming languages from JavaScript and Python to less common ones like Go and Ruby. This makes it incredibly versatile for teams working across different tech stacks.

3. Integration with Visual Studio Code

Seamless integration with Visual Studio Code means that using GitHub Copilot doesn't require switching between tools or disrupting your workflow. It’s right there in the IDE, where you can use it naturally as you code.

4. Automated Refactoring

Copilot can suggest refactoring’s for existing code to improve readability and efficiency. It's like having an automated code review tool that not only spots potential issues but also offers fixes in real time.

Example:

# Original code:
for i in range(len(data)):

    process(data[i])

# Copilot suggestion to refactor:

for item in data:

    process(item)

5. Learning and Adaptation

GitHub Copilot learns from the code you write, adapting its suggestions to better fit your coding style and preferences over time. This personalized touch means it gets more useful the more you use it.

6. Docstring Generation

For those who dread writing documentation, Copilot can generate docstrings based on the code you’ve just written, helping you keep your documentation up-to-date with less effort.

Example:

# Function:
def add(x, y):
    return x + y
# Copilot generates docstring:
"""
Adds two numbers together.
Parameters:
x (int): The first number.
y (int): The second number.
Returns:
int: The sum of x and y.
"""

7. Direct GitHub Integration

Being a product of GitHub, Copilot integrates directly with your repositories, which can streamline the coding process by pulling in relevant context or even whole codebases for better suggestions.

Ending thoughts on Copilot?

GitHub Copilot is more than just a flashy tool; it's a practical, innovative assistant that can significantly enhance the efficiency and enjoyment of coding. It offers a blend of features tailored to improve coding speed, learning, and code quality, while also handling some of the more mundane aspects of programming.

However, it's crucial to approach Copilot with a balanced perspective. While it's an excellent tool for speeding up development and learning new code patterns, it's not a replacement for a deep, fundamental understanding of programming concepts. Over-reliance on such tools can lead to a superficial grasp of coding practices, potentially compromising code quality if suggestions are not properly reviewed.

Therefore, developers should use Copilot as a complement to their skills, not as a crutch.

Want to see where it lags behind HyperTest? Take a look at this comparison page and decide your next-gen testing tool with capabilities that goes beyond the routine AI code-completion tools.