rr

# Overview

[![Build and test status](https://github.com/rr-debugger/rr/actions/workflows/build-and-test-main.yml/badge.svg?branch=master)](https://github.com/rr-debugger/rr/actions)

rr is a lightweight tool for recording, replaying and debugging execution of applications (trees of processes and threads).
Debugging extends gdb with very efficient reverse-execution, which in combination with standard gdb/x86 features like hardware data watchpoints, makes debugging much more fun. More information about the project, including instructions on how to install, run, and build rr, is at [https://rr-project.org](https://rr-project.org). The best technical overview is currently the paper [Engineering Record And Replay For Deployability: Extended Technical Report](https://arxiv.org/pdf/1705.05937.pdf).

Or go directly to the [installation and building instructions](https://github.com/rr-debugger/rr/wiki/Building-And-Installing).

Please contribute!  Make sure to review the [pull request checklist](/CONTRIBUTING.md) before submitting a pull request.

If you find rr useful, please [add a testimonial](https://github.com/rr-debugger/rr/wiki/Testimonials).

rr development is sponsored by [Pernosco](https://pernos.co) and was originated by [Mozilla](https://www.mozilla.org).

# System requirements

* Linux kernel >= 4.7 (for support of `__WALL` in `waitid()`)
  * rr 5.6.0 worked with kernel 3.11 (requiring `PTRACE_SETSIGMASK`)
* rr currently requires either:
  * An Intel CPU with [Nehalem](https://en.wikipedia.org/wiki/Nehalem_%28microarchitecture%29) (2010) or later microarchitecture.
  * Certain AMD Zen or later processors (see https://github.com/rr-debugger/rr/wiki/Zen)
  * Certain AArch64 microarchitectures (e.g. ARM Neoverse N1 or the Apple Silicon M-series)
* Running in a VM guest is supported, as long as the VM supports virtualization of hardware performance counters.
  * Some configurations of VMware and KVM are known to work.
  * Some configurations of AWS and GCP VMs are known to work.
  * No configurations of Xen are known to work.

# AI usage policy

When submitting issues or PRs, please clearly indicate how LLMs were used. Issues or PRs which appear LLM-generated but carry no such indications may be closed without comment.

When submitting PRs for review, the submitter must be human and take full responsibility for understanding the changes, regardless of how LLMs were used.