How Would GitHub Copilot Impact the Software Development Industry?

When GitHub previewed the world’s first AI-powered code completion tool in 2021 called GitHub Copliot, everyone wanted to know its capabilities. This ambitious tool had already surprised many with its accuracy in converting natural language into code, and many believed it could make programming fun.

Two years later, GitHub Copilot has helped over 1 million developers become more productive by assisting them in writing code up to 55% faster. Also, around 400 organizations use GitHub Copilot as an AI pair programmer to help developers code quicker and reduce time-to-market.

Now, as GitHub takes GitHub Copilot further with GitHub Copilot for Business, making it available for every programmer, team, and agency for Software Development – everyone wants to ask the same question:

“What might be the effect of GitHub Copilot on the Software Industry? Would it become the big thing after GPT3?”

In this blog, we’ll reflect on what GitHub Copilot is and how it would transform the software development industry. Let’s begin:

What is GitHub Copilot?

GitHub Copilot is an AI-powered code generation tool created by GitHub in collaboration with Open AI. It uses machine learning to analyze the code in the context of the project you’re working on and generate related code suggestions.

GitHub Copilot can generate code in various programming languages like Python, JavaScript, TypeScript, Ruby, and Go. It can also suggest entire functions, classes, and files based on the developer’s coding habits and the codebase they’re working on. The idea is to make developers more productive by reducing their time on repetitive tasks like writing boilerplate code or looking up documentation.

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GitHub Copilot is powered by Codex, a descendent of the popular language prediction model GPT-3. The only difference is that unlike GPT-3, which is a jack-of-all-trade, Codex is trained for only one purpose, i.e., coding.

What can GitHub Copilot do?

The primary purpose of GitHub Copilot is to read and analyze the code to make code suggestions from within the editor as they type. Unlike IntelliSense, which also auto-completes methods and variable names, GitHub Copilot understands the file’s context to provide comprehensive suggestions. Also, the AI tool constantly adapts to your coding style based on your accepted or rejected edits.

GitHub Copilot can also transform descriptive comments into blocks of code. It benefits people with little coding expertise or working with a language or framework they’re unfamiliar with. Copilot can also save you the time you must spend searching Google or reviewing documentation.

Here are a few scenarios in which GitHub can prove helpful:

• Building components and writing blocks of code.
• Suggesting correct data types to use in your code.
• Auto-filling repetitive code if it senses a pattern. It means you don’t have to write the same code repeatedly, saving time and effort.

Benefits of GitHub Copilot

Here’s how GitHub Copilot can benefit developers:

• GitHub Copilot can save developers time and increase productivity by suggesting code snippets and completing entire functions.
• GitHub Copilot reduces errors that might otherwise be introduced due to manual coding through accurate coding suggestions.
• GitHub Copilot can help improve code quality by suggesting best practices and coding patterns.
• Developers can learn new coding techniques and practice from GitHub Copilot coding suggestions.
• Since GitHub Copilot suggests code consistent with the project’s coding practices, it can help teams collaborate more efficiently.
• GitHub Copilot can make coding more accessible to new developers who may not have as much experience with specific languages or frameworks.

Drawbacks of GitHub Copilot

Despite offering compelling benefits, GitHub Copilot has several significant drawbacks. Here are the aspects where the AI tool lacks:

• Occasionally GitHub Copilot gets the basic syntax wrong and generates code that only works correctly with further adjustments.
• There are times when GitHub Copilot invokes functions and variables that were not defined in the first place, such as the functions that fit the code context but are not there in the codebase. Reason? GitHub analyzes the current file’s content, not the other files in the codebase. Thus, the code may look correct but breaks while compiling.
• Since GitHub Copilot was trained on public repositories, it can only offer suggestions to get things done rather than providing the best way to perform them. Also, the code examples it was trained on could need to be updated.

However, with the current GitHub Copilot for Businesses, GitHub has tried resolving all these issues. The new GitHub Copilot version brings several further improvements to the board, such as

• A powerful AI model that offers better code suggestions to help you write quality code.
• AI-based vulnerability filtering automatically blocks common insecure code suggestions to eliminate issues like SQL injections, path injections, and hardcoded credentials.

Does GitHub Copilot Have Any Ethical Implications?

Yes, GitHub Copilot has several ethical implications, such as:

• Since GitHub Copilot uses code from publicly available sources to generate code suggestions, there’s a concern about intellectual property and copyright infringement.
• GitHub Copilot was trained on biased code. If so, it would only generate biased code suggestions that may result in limited code suggestions, leading to severe consequences. Especially in YMYL (Your Money or Your Life) sectors like Finance, health, and criminal justice – a biased code can lead to the loss of millions or even the loss of life.
• Some malicious actors may use GitHub copilot to generate code that contains security vulnerabilities or exploits – resulting in incidents like data theft, security breaches, and cyber-attacks.

Here’s what you can do to eliminate these ethical implications while using GitHub Copilot:

• Take proper measures to ensure the generated code doesn’t violate copyrights or patents. Give credit to original authors where it’s due. It boosts their confidence and ensures they don’t feel disheartened when their work is used without recognition.
• Ensure that your code is free from any biases. Even if you use GitHub Copilot as a pair programmer and the AI tool has the necessary filters to eliminate and prevent biases, you must ensure your code is free from biases.
• Thoroughly review and test the code generated by GitHub Copilot to ensure it is secure and has no loopholes that anyone can exploit in the future.

In Conclusion

Fire is one of the most beautiful inventions by humans. It can be beneficial or destructive, depending on how you want to use it. AI is also the same. In the right hands, tools like GitHub Copilot can revolutionize the software development industry. They can make developers more productive and help you release high-quality software faster. The AI tool can adapt to individual coding styles and conventions.

However, like other tools, GitHub Copilot could be better. It has its own set of drawbacks that you need to consider before using it as a pair programming tool. Consider the ethical implications that may arise and take steps to address them before the code goes into production.

Also, to answer the most asked question: Will GitHub Copilot replace developers’ jobs? It wouldn’t, especially not for those who can use the tool to their advantage. It would only make their work more fun and help them become more productive.

Although, developers need to spend more time reading and double-checking their code before it goes to production. They need to understand what the generated code is doing rather than blindly following code suggestions.

What do you think? How would GitHub Copilot evolve the software development industry? Please let us know in the comments.

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