Metadata-Version: 2.4
Name: fandango-fuzzer
Version: 1.1.0rc2
Summary: Fandango produces myriads of high-quality random inputs to test programs, giving users unprecedented control over format and shape of the inputs.
Author-email: José Antonio Zamudio Amaya <jose.zamudio@cispa.de>, Marius Smytzek <marius.smytzek@cispa.de>, Andreas Zeller <andreas.zeller@cispa.de>
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Project-URL: homepage, https://fandango-fuzzer.github.io/
Project-URL: repository, https://github.com/fandango-fuzzer/fandango/
Project-URL: Bug Tracker, https://github.com/fandango-fuzzer/fandango/issues
Classifier: Intended Audience :: Science/Research
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Classifier: Programming Language :: Python :: 3.13
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Testing
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Dynamic: license-file

# Generating Test Inputs and Interactions with Fandango

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Welcome to Fandango!
Fandango is a _generator_ of inputs and interactions for software testing.
Given the specification of a program's input or interaction language, Fandango quickly generates myriads of valid sample inputs for testing.

The specification language combines a _grammar_ with _constraints_ written in Python, so it is extremely expressive and flexible.
Most notably, you can define your own _testing goals_ in Fandango.
If you need the inputs to have particular values or distributions, you can express all these right away in Fandango.

Fandango supports multiple modes of operation:

* By default, Fandango operates as a _black-box_ fuzzer - that is, it creates inputs from a `.fan` Fandango specification file.
* If you have _sample inputs_, Fandango can _mutate_ these to obtain more realistic inputs.
* Fandango can also produce _interactions_ for _protocol fuzzing_ - that is, it acts as a client or server producing and reacting to interactions according to specification.

Fandango comes as a portable Python program and can easily be run on a large variety of platforms.

Under the hood, Fandango uses sophisticated _evolutionary algorithms_ to produce inputs,
it starts with a population of random inputs, and evolves these through mutations and cross-over until they fulfill the given constraints.

Fandango is in active development! Features planned for 2026 include:

* coverage-guided testing
* code-directed testing
* high diversity inputs

and many more.

For the complete Fandango documentation, including tutorials, references, and advanced usage guides, visit the [Fandango documentation](https://fandango-fuzzer.github.io/)

---

## License

Fandango is licensed under the European Union Public Licence V. 1.2. See the [LICENSE](https://github.com/fandango-fuzzer/fandango/blob/main/LICENSE.md) file for details.
