> For the complete documentation index, see [llms.txt](https://tools.galois.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://tools.galois.com/saw/crux/what-is-crux.md).

# What is Crux?

Crux is a tool for improving the assurance of software using **symbolic testing**, currently supporting C/C++ and Rust. Crux can provide you with additional assurance that your code does what you want it to do, and provides higher coverage of possible inputs than techniques such as randomized fuzzing or unit testing.

Specifically, Crux uses symbolic reasoning to check tests **exhaustively**, on all possible inputs, rather than on a smaller number of fixed or randomly-chosen values. In this way, Crux improves the coverage possible with [property-based testing](https://www.drmaciver.com/2016/03/the-easy-way-to-get-started-with-property-based-testing/), a popular approach supported by [libraries](https://github.com/silentbicycle/theft) [for](https://en.wikipedia.org/wiki/QuickCheck) [many](https://blog.logrocket.com/property-based-testing-in-rust-with-proptest/) [languages](https://jsverify.github.io/).

Crux can:

* Perform **symbolic** reasoning to evaluate tests **exhaustively**
* Analyze **C/C++** and **Rust** code
* Generate **counter-examples** when tests fail
* Generate **executable** versions of counter-examples to load in a debugger
* Generate **complete** models of programs to comprehensively rule out failure cases

Crux is available open-source under the 3-Clause BSD License [on GitHub](https://github.com/GaloisInc/crucible).


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://tools.galois.com/saw/crux/what-is-crux.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.