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https://github.com/agroce/universalmutator

Regexp based tool for mutating generic source code across numerous languages
https://github.com/agroce/universalmutator

c cpp fe-language golang golang-tools java language multi-language mutant mutation mutation-testing mutations python regexp rust solidity-language swift testing vyper

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Regexp based tool for mutating generic source code across numerous languages

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README 

        
This is a tool based on source-based rewrite of code lines for mutation generation, including

multi-language rules aided by special rules for languages or even projects.  Originally, the approach used only regular expressions,

treating code as text.  However, there is also a mode that can use the [Comby](https://github.com/comby-tools/comby) tool

for more sophisticated mutation that produces fewer invalid mutants.  Regular-expression based mutation works well, in our experience;

comby-aided mutation works even better.  The key advantage of either approach is that the tool can probably mutate approximately *any* interesting source code you have, and language changes don't force

rewriting of the mutation tool.  To use the comby mode, just make sure comby is installed and add `--comby` when you run `mutate`.



More information on this project can be found in a [2024 FSE paper](https://agroce.github.io/fse24.pdf), and in the original [2018 ICSE Tool Paper](https://agroce.github.io/icse18t.pdf).



A [guest blog post](https://blog.trailofbits.com/2019/01/23/fuzzing-an-api-with-deepstate-part-2/) for Trail of Bits shows how to use the universalmutator to help improve a C/C++ API fuzzing effort using [DeepState](https://github.com/trailofbits/deepstate) and libFuzzer.



The universalmutator has support for extracting coverage information to guide mutation from the [TSTL](https://github.com/agroce/tstl) testing tool for Python.



HOW TO USE IT

=============



To use this, you should really just do:



`pip install universalmutator`



then



`mutate --help`



SIMPLE EXAMPLE USAGE

====================



`mutate foo.py`



or



`mutate foo.swift`



should, if you have the appropriate compilers installed, generate a bunch of valid, non-trivially redundant, mutants.



A MORE COMPLEX EXAMPLE

======================



Sometimes the mutated code needs to be built with a more complicated command than a simple compiler call, and of course you want help discovering which mutants are killed and not killed.  For example, to mutate and test mutants for the mandelbrot plotting example included in the PROGRAMMING RUST book (http://shop.oreilly.com/product/0636920040385.do), just do this:



    git clone https://github.com/ProgrammingRust/mandelbrot

    cd mandelbrot

    cargo build

    target/debug/mandelbrot origmandel.png 1000x750 -1.20,0.35 -1,0.20

    mkdir mutants

    mutate src/main.rs --mutantDir mutants --noCheck

    analyze_mutants src/main.rs "cargo clean; cargo build; rm mandel.png; target/debug/mandelbrot mandel.png 1000x750 -1.20,0.35 -1,0.20; diff mandel.png origmandel.png" --mutantDir mutants



(It will go faster if you edit `main.rs` to lower the maximum number of threads used to something like 8, not 90.) At the moment, this won't use any Trivial Compiler Equivalence, but still kills about 60% of the 1000+ mutants. The killed mutant filenames will be in `killed.txt` and the non-killed ones in `not-killed.txt`.



Working with something like maven is very similar, except you can probably edit the complicated build/clean stuff to just a 'mvn test' or similar.



CURRENTLY SUPPORTED LANGUAGES

=============================



The tool will likely mutate other things, if you tell it they are "c" or something, but there is auto-detection based on file ending and specific rule support for:



```

C

C++

Java

JavaScript

Python

Swift

R

Rust

Go

Lisp

Fortran

Solidity

Vyper

Fe

```



(the last three are smart contract languages for the Ethereum blockchain).



All but C, C++, JavaScript, and Go will try, by default, to compile the mutated

file and use TCE to detect redundancy.  Of course, build dependencies

may frustrate this process, in which case --noCheck will turn off TCE

and just dump all the mutants in the directory, for pruning using a

real build process.  In the long run, we plan to integrate with

standard build systems to avoid this problem, and with automated test

generation systems such as TSTL (https://github.com/agroce/tstl) for

Python or Echidna for Solidity

(https://github.com/trailofbits/echidna).  Even now, however, with

`analyze_mutants` it is fairly easy to set up automatic evaluation of

your automated test generator.



MUTATING SOLIDITY CODE

======================



The universalmutator has been most frequently applied to smart

contracts written in the Solidity language.  It supports a few special

features that are particularly useful in this context.



First,

Solidity libraries are often written with only `internal` functions

--- and the compiler will not emit code for such functions if you

compile a library by itself, resulting in no non-redundant mutants.

In order to handle this case, `mutate` can take a `--compile` option

that specifies another file (a contract using the library, or the

tests in question) that is used to check whether mutants are

redundant.



Second, swapping adjacent lines of code is a seldom-used mutation

operator that is unusually attractive in a Solidity context because

swapping a state-changing operation and a requirement may reveal that

testing is incapable of detecting some

[re-entrancy](https://github.com/crytic/not-so-smart-contracts/tree/master/reentrancy)

vulnerabilities.  The testing may notice the absence of the check, but

not a mis-ordering, and these mutants may reveal that.  To add code

swaps to your mutations, just add `--swap` to the `mutate` call.  Note

that swaps work in any language; they are just particularly appealing

for smart contracts.



MORE INFORMATON

===============



For much more information, again see https://agroce.github.io/icse18t.pdf -- demo/tool paper at ICSE 18 and especially our full FSE 2024 paper -- https://agroce.github.io/fse24.pdf -- the latter discusses the latest version of the tool/approach, and includes a comparison with many other mutation testing tools.



The aim of this project is partly to see how quickly mutation can be applied to new languages, partly how much the work of a tool can be

offloaded to the compiler / test analysis tools.



Authors:  Alex Groce, Josie Holmes, Darko Marinov, August Shi, Lingming Zhang, Kush Jain, Rijnard van Tonder, Sourav Deb