# Debugging Rust in 2026: Tools and Techniques

An analysis of evolving Rust debugging workflows from print statements to AI-assisted IDE integration.

- **Source:** [The JetBrains Blog](https://brifing.si/source/782eebd1-7be8-49cc-b27c-e552516691b2)
- **Published:** 2026-11-10
- **Topic:** [technology](https://brifing.si/c/technology)
- **Original article:** <https://blog.jetbrains.com/rust/2026/11/10/debugging-rust/>
- **On Brifing:** https://brifing.si/s/b239de52-0b73-4650-94fb-d8c6afda7ff1

## Current State of Debugging

The 2026 Rust debugging survey reveals that 53.2% of users avoid traditional debuggers entirely. Instead, 81.3% of developers prefer print-based debugging due to its simplicity. Despite these trends, debugger adoption has grown from 36% in 2021 to 46.8%, indicating a slow but steady shift toward more sophisticated tooling in the ecosystem.

## The Print Debugging Loop

Using println! or dbg! macros remains the most common method for identifying bugs in Rust. While effective for small programs, this approach is tedious for larger projects. It requires constant recompilation and manual inspection of output, which significantly slows down the development cycle compared to interactive debugging tools available in other languages.

## Terminal-Based Debugging Tools

Developers can utilize rust-gdb or rust-lldb directly in the terminal to inspect failing tests without modifying source code. By setting breakpoints and examining frames, programmers can identify logic errors like incorrect distance comparisons. This method provides deeper state visibility than print statements but requires manual effort to manage complex debugger commands.

## Visualizing Algorithms with TUIs

Text User Interfaces, such as those built with Ratatui, offer a visual way to debug complex algorithms like the Graham scan. By visualizing the convex hull computation, developers can immediately spot where the logic fails to enclose points. This visual feedback loop complements traditional debugging by providing an intuitive representation of runtime data.

## RustRover IDE Integration

RustRover provides a graphical interface for GDB and LLDB, simplifying the debugging experience for Rust developers. It integrates Cargo projects and code analysis into a single environment. The IDE lowers Rust expressions to MIR, allowing the debugger to execute code against a paused process, bridging the gap between high-level code and execution.

## AI-Assisted Debugging Workflows

Starting with RustRover 2026.3, developers can use the Model Context Protocol to connect AI agents like Codex or Claude Code. These agents can autonomously start debug sessions, set breakpoints, and evaluate expressions. This integration allows the AI to assist in identifying and fixing bugs directly within the IDE's managed environment.

## Technical Challenges in Debugging

Debugging Rust remains difficult due to the language's complexity, particularly with async code and macros. Approximately 28.1% of users struggle with async debugging, while 23.0% face issues with macros. These features often cause stepping functions to break, making it challenging for beginners to adopt formal debuggers over simpler, more reliable print-based methods.

## Choosing the Right Workflow

There is no single best way to debug Rust; the choice depends on project scale and developer preference. While print statements suffice for quick checks, IDEs and AI agents provide powerful alternatives for complex issues. Ultimately, developers should select the tool that best balances their need for speed and deep state inspection.

## Sources covering this story

- https://blog.jetbrains.com/rust/2026/11/10/debugging-rust/ — 

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_Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._