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GitHub Copilot
The World’s Most Widely Adopted AI Developer Tool
Official Website https://github.com/features/copilot
GitHub Copilot is a cloud-based artificial intelligence tool developed by GitHub and OpenAI to assist users of Visual Studio Code, Visual Studio, Neovim, and JetBrains IDEs by auto-completing code. Currently available by subscription to individual developers and to businesses, the tool was first announced by GitHub on 29 June 2021, and works best for users coding in Python, JavaScript, TypeScript, Ruby, and Go.
In which phase of work flow it is involved:
¶ Feature Highlights
¶ Start a Conversation about Your Codebase
Improve code quality and security. Developers feel more confident in their code quality when authoring code with Copilot. And with the built-in vulnerability prevention system, insecure coding patterns get blocked in real time.
Enable greater collaboration. Copilot indexes and understands your repositories so developers can quickly ramp into new codebases, improve legacy code, and build off each other’s work.
Relevant Use Cases:
Scrum Activities: Writing Code with the Assistance of GitHub Copilot
Scrum Activities: Debugging with GitHub Copilot
Scrum Activities: Writing Unit Test with AI Assistant
Scrum Activities: GitHub Copilot Workspace Feature Intro
¶ Get AI-based Suggestions in Real-time
GitHub Copilot suggests code completions as developers type and turn natural language prompts into coding suggestions based on the project's context and style conventions.
Constraints:
GitHub Copilot can suggest code that is inefficient, unoptimized or even insecure, which requires developer's verification.
Henkel's legal team may need to determine if there is a licensing issue with the suggested code.
¶ Ask for Assistance Right in Your Terminal
GitHub Copilot in the CLI provides a chat-like interface in the terminal that allows you to ask questions about the command line. You can ask GitHub Copilot to provide either command suggestions or explanations of given commands.
GitHub Copilot in the CLI parses your question and provides an answer using a combination of natural language processing and machine learning. This process can be broken down into a number of steps.
¶ More Features with Potential
¶ Docs that Feel Tailored for You
Spend less time searching and more time learning, by getting personalized answers that are grounded in your organization’s documentation, with inline citations. Load content → Ask questions → Profit.
¶ Pull Requests That Tell a Story
GitHub Copilot keeps track of your work, suggests descriptions, and helps reviewers reason about your changes.
Notes: Features listed in this section are offered via GitHub Copilot Enterprise and are not publicly available in 2023.
¶ Read More
Get Started with the Future of Coding: GitHub Copilot
¶ Implication to Henkel Team
¶ How You Should React
GitHub Copilot might be one of the best dev tools powered by generative AI. It is suggested that all the development team members should be encouraged to employ this tool in the daily workflow.
Potential next steps:
- Evaluation: Perform the assessment carefully to ensure the use of GitHub Copilot is regulatory compliance within Henkel, including data handling, suggested code ownership and licensing, etc.
- Team Learning Sessions: Organize regular training sessions for team members to familiarize them with GitHub Copilot's features and capabilities.
- Gradual Integration: Start by integrating Copilot into smaller, non-critical projects to allow team members to get hands-on experience. Gradually increase its use as comfort and proficiency grow.
- Revise Development Processes: Modify existing development workflows to include stages where GitHub Copilot's input is evaluated and refined. This might involve additional code reviews or pairing sessions focused on AI-generated code.
¶ Impact & Benefit
- Increased Developer Productivity: GitHub Copilot accelerates coding by suggesting code snippets and completing lines, allowing developers to focus on complex tasks and speeding up project completion.
- Enhanced Code Quality and Learning: It offers high-quality code suggestions based on a vast repository, introducing developers to new coding patterns and best practices, beneficial for continuous learning and skill improvement.
- Support for Multiple Languages and Frameworks: GitHub Copilot's compatibility with various programming languages and frameworks makes it a versatile tool for diverse technology projects, enhancing development efficiency across different teams.
¶ Constraints about GitHub Copilot
¶ Data Privacy
Since GitHub Copilot operates by sending snippets of code to its servers for analysis, there could be concerns about sensitive or proprietary code being exposed.
Although GitHub claims that the uploaded code is encrypted and the code will be deleted immediately after the code suggestion is generated.
¶ Intellectual Property and Licensing Risks
The code suggested by GitHub Copilot is derived from publicly available sources, which may include code snippets with specific licenses. This raises concerns about inadvertently incorporating copyrighted or licensed code into proprietary projects, potentially leading to legal issues.
¶ Code Quality and Reliability
GitHub Copilot's suggestions are based on patterns it has learned from a vast codebase, but they may not always be accurate or optimal. This can lead to concerns about the reliability and quality of the suggested code, especially in complex or critical systems.