Unlocking endless web development potential with CoPilot

In this modern age of web development, both enterprises and developers themselves are striving to find ways to improve various aspects of the web development process like productivity, quality, time, efficiency etc. and still be in line with the industry standards and best practices. Until recently developers were reliant on various open source plugins or extensions available for each integrated development environment (IDE) for ensuring bad code injections are caught along with small suggestions on certain aspects of development such as importing from correct path or rectifying a syntax issue.

However, the launch of GitHub Copilot by OpenAI has brought in a positive disruption in this space. GitHub Copilot is an AI based tool that provides intelligent suggestions and recommendations to the developers in their day to day development. GitHub Copilot is not just another IDE extension that provides lint errors and formatting suggestions, but rather it understands the current code base and provides the developer with a set of recommendations which it deemed suitable. The developer is now free to choose the right option from the list of suggestions and the GitHub Copilot will learn from this exchange. When a similar nature of code appears next, GitHub Copilot will take into account the previous developer choice and provides the new recommendation.

During the launch of GitHub Copilot, there were serious concerns about accuracy, data security etc., but all have been thwarted away and GitHub Copilot has been adopted by the development community with both hands. GitHub Copilot has proved to be accurate for modern frameworks and languages as it boasts training dataset of all of publicly available GitHub repositories. The underlying AI-ML model is continuously learning and there aren’t any competitors that have a product that is anywhere close to GitHub Copilot in terms of efficiency. GitHub Copilot can be integrated into all major IDEs that are popular in the development community right now. GitHub Copilot seamlessly integrates into various code editors like Neovim, JetBrains IDEs, Visual Studio, and Visual Studio Code. It operates with remarkable speed, allowing you to utilize it in real-time as you type.

Getting Started with Copilot

From a web development stand-point, GitHub Copilot is best suited assistant for a developer and the scenarios where it becomes a peer programmer is numerous. Even though GitHub OpenAI based Copilot is not a magic wand that creates web applications in a single shot, it still serves as a proficient personal assistant enhancing the developer efficiency. Copilot significantly enhances this process by providing valuable code suggestions, snippets, and contextual advice. Following are the high level scenarios where GitHub Copilot can be deemed very useful for web developers:

Creating HTML templates with CSS

In web development projects, HTML templates serve as the foundation for websites, and GitHub Copilot can be employed right from the initial creation of the HTML skeleton. The recommendations it provides typically require only minimal adjustments, and the quality of suggestions improves as you progress with your development. Here are some sample prompts and their corresponding suggestions obtained from Copilot:

Similarly, this capability can be extended to the creation of various types of HTML components, complete with corresponding CSS styles.

Using CSS frameworks like Bootstrap, Tailwind or Foundation

Developers can effortlessly incorporate their preferred CSS frameworks by using a straightforward prompt, like “Include the Bootstrap framework.” GitHub Copilot will then suggest the appropriate CSS framework hosted via a Content Delivery Network (CDN). After the framework is added to the project, GitHub Copilot will autonomously identify it and commence providing recommendations for HTML and CSS based on the Bootstrap framework.

Developing SPA via Angular, React or Vue

Copilot is best suited for developing SPA using frameworks like Angular, React, Vue and other similar ones. GitHub Copilot is useful for creating routes, creating methods, completing the right imports, applying the right dependency injections and many more. The beauty is that GitHub Copilot will be able to instantly prompt you with a method or a function if its defined in any of the dependent packages. You have easy access to code snippets that are single line to sufficiently large and complex snippets as well.

Writing Unit test cases with JEST

GitHub Copilot offers a major advantage through its effortless assistance with unit test case completion. Although it may not deliver pinpoint accurate test cases for all conceivable scenarios, it steadily improves the quality of its suggestions as it learns and evolves with time. This feature can be invaluable for developers seeking to streamline the testing process and enhance the reliability of their codebase. While GitHub Copilot is efficient in writing or completing unit test cases for JavaScript or TypeScript based front-end web applications, the same may not be said about other technologies or languages like Java, C# etc.

Conclusion

While GitHub Pilot comes a long way from the traditional days of tooltips and hints of IDEs, the developer would still be required to do the due diligence in ensuring that the code prompted by GitHub Copilot is following the security best practices and standards in order to avoid any vulnerabilities and degrading the code quality of the project. One also has to ensure that proper code reviews and testing is done regularly to ensure the code remains clean, free of defects and be of the highest in terms of quality standards.

As an AI pair programmer, GitHub Copilot is indeed a revolution in the industry and has significantly brought about a disruption in this space. One can only look eagerly towards the future to see how GitHub Copilot evolves in the new age rush into AI technologies.

As an AI-powered pair programmer, GitHub Copilot represents a ground-breaking transformation within the industry, introducing a substantial disruption in conventional practices. The anticipation surrounding the future of GitHub Copilot is palpable, as it propels us into a thrilling era characterized by rapid advancements in AI technologies. Watching how GitHub Copilot evolves and adjusts in this ever-changing environment is a source of tremendous fascination and enthusiasm for both developers and the broader technology community and one can eagerly look towards what the future holds for the web development community and GitHub Copilot.

Reference

Author Details

Roy Maria John

Roy M J is a Technology Architect with Infosys. He is a Digital Transformation Specialist associated with Digital Experience IP Platforms & Frameworks in Infosys. He helps in delivering digital transformation for large enterprises across the globe via Live Enterprise Interactions Suite and Digital Marketplace Platforms. He has rich experience in Web technologies primarily on the JavaScript stack. He is part of Cloud and Emerging Technologies track in the Digital Technology Council.

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