GitHub Copilot assists in the requirements analysis phase primarily by aiding in the documentation process. Through its chat interface, developers can ask Copilot to generate templates for requirements artifacts such as user stories, use cases, or behavior-driven development (BDD) scenarios in formats like Gherkin or Markdown. It can also produce code snippets or data structure definitions that help clarify technical specifications within the requirements documents. This leverages Copilot's core capability of turning natural language prompts into structured text and code, thereby accelerating the documentation aspect of requirements analysis.

A. By automatically generating detailed requirements documents.

Copilot lacks the high-level project context, business domain knowledge, and stakeholder inputs to automatically generate a complete, detailed requirements document from scratch.

C. By identifying and fixing potential requirement conflicts when using /help.

The /help command in GitHub Copilot Chat provides instructions on how to use Copilot itself; it is not a feature for analyzing or resolving conflicts in software requirements.

D. By managing stakeholder communication and meetings.

GitHub Copilot is an AI pair programmer and developer tool, not a project management or communication platform. It has no features for managing meetings or stakeholder interactions.

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1. GitHub Docs, "Using GitHub Copilot Chat in your IDE." This official documentation outlines the capabilities of Copilot Chat. It states that users can "get answers to coding-related questions" and "write documentation." This supports the use of Copilot for generating documentation templates and snippets, which is a key activity in the requirements analysis phase. The /doc slash command is a specific feature designed for documentation assistance.

Source: GitHub, Inc. (2024). Using GitHub Copilot Chat in your IDE. GitHub Docs. Retrieved from https://docs.github.com/en/copilot/github-copilot-chat/using-github-copilot-chat-in-your-ide.

2. GitHub Docs, "About GitHub Copilot." This document describes Copilot's fundamental function as turning natural language prompts into suggestions. This core capability is not limited to code; it can be applied to generate structured text for documentation based on a developer's prompt, such as "Create a template for a user story about a login page."

Source: GitHub, Inc. (2024). About GitHub Copilot. GitHub Docs. Retrieved from https://docs.github.com/en/copilot/overview-of-github-copilot/about-github-copilot.

3. Vaithilingam, P., Tian, G., & Fu, P. (2022). "Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models." 2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pp. 1-6. This peer-reviewed paper discusses how developers use AI coding tools. While focused on code generation, it notes that these tools are used for "scaffolding" and creating "boilerplate," a principle that extends to generating templates for documentation, which is a form of scaffolding for the requirements process.

DOI: https://doi.org/10.1109/VL/HCC53370.2022.9833101