AI-assisted debugging with GitHub Copilot

Debugging remains one of the most time-intensive parts of development. GitHub Copilot aims to shorten that process by helping you analyze, fix, and document code across multiple surfaces—your IDE, github.com, and pull requests. The free tier of GitHub Copilot is available to all personal accounts, so you can explore these capabilities without upgrading.

Where Copilot fits in your debugging workflow

Copilot works by recognizing patterns and suggesting solutions based on what it has learned from training data. The practical approach, according to GitHub Senior Developer Advocate Christopher Harrison, is to first identify the problem area yourself, then ask Copilot something like: "I'm giving this input but getting this output—what's wrong?" The assistant is most useful when pointed at a specific issue.

In the IDE

Within VS Code, JetBrains, and other supported editors, Copilot offers real-time assistance as you type:

  • Issue detection: Declare a variable without initializing it and Copilot may suggest a correction before you run the code.
  • Syntax fixes: Errors in your code can be resolved with a suggested correction in seconds.
  • Context-aware help: Copilot analyzes your workspace and provides solutions tailored to your project structure.

In Copilot Chat

Copilot Chat functions as an interactive debugging assistant using natural language. With the free plan you get 50 chat messages per month. Useful patterns include:

  • Asking "Why is this function throwing an error?" to get an explanation of the underlying problem.
  • Using slash commands like /fix to generate solutions or /explain for a step-by-step breakdown.
  • Requesting refactoring suggestions when code is messy or inefficient. As Harrison notes, cleaner code is easier for both humans and AI to read, which makes future debugging simpler.
  • Describing an issue in plain language and receiving tailored guidance without leaving the editor.

On github.com

Copilot Chat also works directly in repositories and discussions on github.com. You can highlight a problematic section of a file and ask for analysis, request test case suggestions for verifying a function, or ask for summaries of unfamiliar code in open-source projects and teammates' PRs.

In pull requests

Copilot can help maintain code quality during the PR review process:

  • Suggested improvements: Copilot reviews PRs and proposes fixes in the conversation thread.
  • PR summaries: Greg Larkin, Senior Service Delivery Engineer, uses Copilot when creating PRs to generate a summary of changes between his feature branch and the target branch—particularly helpful when he's stuck on writing a description others will understand.
  • Diff explanations: Ask Copilot to summarize what changed between commits when the rationale isn't obvious.
  • Pre-merge checks: The /analyze command identifies potential issues and /tests generates missing test cases.
  • On-the-fly refactoring: Redundant or inefficient code in a PR can be flagged with optimized alternatives.

Pair Copilot's PR assistance with peer review—it speeds up the process but shouldn't replace human expertise.

Five slash commands that matter for debugging

Slash commands turn Copilot Chat into an on-demand debugging tool. These are the most useful ones:

/help

Provides guidance on how to interact with Copilot effectively, including tips on structuring prompts and using commands. Type /help in Copilot Chat to get suggestions relevant to your current task, whether you're debugging, explaining code, or generating test cases. It's also a quick way to refresh your knowledge of what commands like /fix and /explain do.

/fix

Resolves code issues by generating suggestions from a highlighted block of code or an error description. Select the problematic code, type /fix, and Copilot Chat will propose a corrected version. For example, a broken API call might come back with the right headers or parameters added.

/explain

Breaks down complex code or cryptic error messages into digestible terms. Highlight the code or error, type /explain, and Copilot will walk through the function's purpose, how it processes data, potential edge cases, and possible bugs. Encounter a NullPointerException? This command can clarify why it occurred and how to prevent it.

/tests

Generates test cases based on the selected code. Testing is a core part of identifying bugs, and /tests on a function or snippet produces relevant cases. Applied to a sorting function, it might generate unit tests for edge cases like empty arrays or null inputs.

/doc

Creates or refines code documentation, which helps both developers and Copilot itself draw context from the codebase. Highlight a function, class, or file, type /doc (or right-click to access the context menu), and Copilot generates comprehensive comments covering purpose, parameters, and expected output. Good documentation makes code more searchable and speeds up future troubleshooting.

Getting More Useful Debugging Responses

GitHub Copilot's debugging suggestions improve dramatically with context. The more it understands about your intent, the more relevant its advice becomes. Copilot analyzes code within the surrounding scope, so keeping files well structured and dependencies included matters. In Copilot Chat, reference specific functions, error messages, or logs to avoid generic answers. For multi-file work, the @workspace command gives Copilot broader context about your prompt and goal.

Treat Debugging as an Iterative Conversation

Avoid treating Copilot as a one-shot tool. Refine its output through back-and-forth questioning. Asking for three or four alternative fixes or performance analyses often surfaces approaches you hadn't considered. Specify constraints like speed or memory efficiency to steer results. This iterative process tends to produce more robust code than accepting the first suggestion.

Write Specific Prompts

The precision of your question directly affects response quality. Instead of "What's wrong with this function?", try "Why is this function returning undefined when the input is valid?" Specific queries work whether you're requesting a fix, an explanation, or test cases. Testing edge cases with detailed prompts can also reveal issues before they reach production.

Use Progressive Debugging

Rather than jumping straight to fixes, work through problems step by step. This structured approach—progressive debugging—means first understanding the issue, then analyzing causes, then implementing a solution. Copilot's slash commands support this workflow:

  1. Run /explain on a problematic function to understand what's happening.
  2. Use /startDebugging to configure interactive debugging.
  3. Apply /fix to generate corrections.

For a React component that isn't rendering correctly, for instance, /explain on the JSX or state logic helps first, then /debug can pinpoint mismanaged props, and /fix provides the corrected implementation.

Combine Commands for Complex Problems

Some bugs need multiple debugging passes. Combining commands moves you from diagnosis to resolution faster:

  • /explain + /fix helps you understand and resolve issues efficiently.
  • /fixTestFailure + /tests locates failing tests and generates new ones.

Slash commands work best when used with clear problem descriptions, as part of a systematic approach, and followed by verification.

AI Assistance Doesn't Replace Human Oversight

GitHub Copilot acts as an additional reviewer, analyzing code and offering comments, but human judgment remains essential. Different perspectives catch different problems, so Copilot's suggestions should be combined with human expertise and rigorous testing. The result is more efficient debugging without sacrificing code quality or reliability.