Each year, thousands of students start studying software development while expert developers are improving themselves to be better in specific fields. Software development is one of the most lucrative fields and it seems like it will continue gaining popularity at least in the near future. While thousands of developers spend hours and money learning programming, on the other hand, tech giants are constantly working on new ways to make programming easier and accessible for everyone. Many companies are working on no-code development platforms allowing users to create application software via a graphical user interface. Also, some companies are developing new tools to help developers to code faster and more efficiently.
GitHub Copilot is GitHub’s cloud-based AI tool that aims to help developers while coding. In a very short time, it showed the capabilities of AI when combined with GitHub’s enormous database of codes. It is the first time in history that AI is harnessed by developers to write and complete code. GitHub Copilot is an editor extension that distills the collective knowledge from its developers to suggest code in real time.
A brief history of GitHub Copilot
GitHub Copilot is a relatively new tool, but it has already gained significant popularity among developers. GitHub Copilot is developed by GitHub, a Microsoft subsidiary, and OpenAI, creator of ChatGPT and Dall E 2. The company announced the technical preview for GitHub Copilot in June of 2021. Within a year, over 1.2 million developers used the new AI tool and in files where Copilot is enabled, approximately 40% of code was written by GitHub Copilot in major coding languages.
GitHub released the GitHub Copilot as a plugin on the JetBrains marketplace and the GitHub Copilot Neovim plugin as a public repository in October of 2021. The technical preview period ended in June of 2022 and the service is currently available as a subscription-based service.
What are GitHub’s Copilot’s capabilities?
In simplest terms, GitHub Copilot uses OpenAI Codex, a machine learning model that focuses on translating natural language into code, to suggest individual lines and whole functions to users while typing. There are various use cases for GitHub Copilot that helps developers to code easier and faster.
GitHub Copilot can understand multiple languages. For example, it can complete comments in different languages and write the required code. It can also translate from English to other languages. Also, programming languages are based on American English, which can be unfamiliar to British or Canadian-English speakers. If a user types the CSS property “colour” instead of “color”, it can cause unexpected errors. Copilot helps developers eliminate that kinds of typos.
GitHub Copilot can also create dictionaries of lookup data. For example, users can instruct the tool to create a dictionary of two-letter ISO country codes and their contributing country names by writing a comment and the first few lines of code to help Copilot.
Writing tests is an important part of the software development lifecycle. Copilot’s pattern recognition and pattern completion capabilities allow developers to write faster unit tests, visual regressions tests, and more.
Users can also write a comment or a function name to trigger suggestions. For example, by typing the “validate a phone number” comment, the tool can create a code to validate a phone number. Ot, it can remove white space from strings.
Users can also navigate a new codebase with Copilot Labs, a complementary extension created by the GitHub Next team. GitHub Copilot Labs, an experimental sidebar, enables users to translate code to another programming language with a step-by-step explanation of code snippets.
How does GitHub Copilot work?
The idea behind Copilot is very similar to many other AI tools. GitHub Copilot is powered by Codex, a version of OpenAI’s GPT-3 model. The main difference between GPT-3 and Codex is that Codex is designed and trained specifically for programming tasks, thus it provides better results. What makes Copilot really efficient is the amount of data or the millions of public code repositories that it was trained on. The data it has gathered makes it possible to predict the next sequence of code, which is very similar to ChatGPT in a way. It works best with Python, JavaScript, TypeScript, Ruby, and Go.
Is GitHub Copilot reliable?
Like any other AI tool, GitHub Copilot is not error-free. If you are trying to learn software development or improve yourself with different languages, Copilot can be a really nice assistant for you. But if your job depends on the code you are writing, we wouldn’t suggest trusting an AI tool 100%. Many examples showed that Copilot can make unusual mistakes from time to time and it can cause vulnerabilities. So, you can use Copilot as an assistant, but since you can’t hold it accountable for the mistakes, you should always double-check the codes it wrote for you.
Is GitHub Copilot a replacement for human programmers?
Although Copilot’s results are fairly accurate, it is not always %100 reliable. It definitely can code faster than humans, but not more effectively in most cases. Thus, it doesn’t seem like it can replace programmers, at least for a while. It is more likely to be an assistant for programmers, as its name also implies. Also, it is trained on repositories made by programmers. Thus, it needs codes that are written by humans to train on and it won’t be able to produce the code for the tasks that it wasn’t trained for yet.
Is GitHub Copilot free?
GitHub Copilot is a subscription-based paid service. For personal use Copilot for Individual costs $10 per month, or $100 per year. Copilot for Business, which includes simple license management, organization-wide policy management, and privacy, costs $19 per user per month.