icontract-hypothesis
fuzz-introspector
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icontract-hypothesis | fuzz-introspector | |
---|---|---|
3 | 2 | |
74 | 346 | |
- | 2.0% | |
0.0 | 9.6 | |
almost 2 years ago | 17 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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icontract-hypothesis
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Automated Unit Test Improvement Using Large Language Models at Meta
https://github.com/mristin/icontract-hypothesis
Nagini and deal-solver attempt to Formally Verify Python code with or without unit tests: https://news.ycombinator.com/item?id=39139198
Additional research:
"Fuzz target generation using LLMs" (2023)
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Adding “invariant” clauses to C++ via GCC plugin to enable Design-by-Contract
https://icontract.readthedocs.io/en/latest/usage.html#invari...
For unit testing, there's icontract-hypothesis; with the Preconditions and Postconditions delineated by e.g. decorators, it's possible to generate many of the fuzz tests from the additional Design by Contract structure of the source.
From https://github.com/mristin/icontract-hypothesis :
> icontract-hypothesis combines design-by-contract with automatic testing.
> It is an integration between icontract library for design-by-contract and Hypothesis library for property-based testing.
> The result is a powerful combination that allows you to automatically test your code. Instead of writing manually the Hypothesis search strategies for a function, icontract-hypothesis infers them based on the function’s [sic] precondition
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Pynguin – Allow developers to generate Python unit tests automatically
Just in case you are looking for an alternative approach: if you write contracts in your code, you might also consider crosshair [1] or icontract-hypothesis [2]. If your function/method does not need any pre-conditions then the the type annotations can be directly used.
(I'm one of the authors of icontract-hypothesis.)
[1] https://github.com/pschanely/CrossHair
[2] https://github.com/mristin/icontract-hypothesis
fuzz-introspector
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Automated Unit Test Improvement Using Large Language Models at Meta
https://google.github.io/oss-fuzz/research/llms/target_gener... https://security.googleblog.com/2023/08/ai-powered-fuzzing-b... https://hn.algolia.com/?q=AI-Powered+Fuzzing%3A+Breaking+the...
OSSF//fuzz-introspector//doc/Features.md: https://github.com/ossf/fuzz-introspector/blob/main/doc/Feat...
https://scholar.google.com/scholar?hl=en&as_sdt=0%2C43&q=Fuz... :
- "Large Language Models Based Fuzzing Techniques: A Survey" (2024) https://arxiv.org/abs/2402.00350 :
- ossf/fuzz-introspector: Fuzz Introspector - help fuzzer developers to get an understanding of their fuzzer’s performance
What are some alternatives?
pynguin - The PYthoN General UnIt Test geNerator is a test-generation tool for Python
AlphaCodium - Official implementation for the paper: "Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering""
CrossHair - An analysis tool for Python that blurs the line between testing and type systems.
oss-fuzz-gen - LLM powered fuzzing via OSS-Fuzz.
Polyester.jl - The cheapest threads you can find!
clang-contracts - Experimental support for contracts programming in clang++