icontract-hypothesis
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icontract-hypothesis | AlphaCodium | |
---|---|---|
3 | 6 | |
74 | 3,050 | |
- | 9.1% | |
0.0 | 8.4 | |
almost 2 years ago | 12 days ago | |
Python | Python | |
MIT License | GNU Affero General Public License v3.0 |
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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
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Automated Unit Test Improvement Using Large Language Models at Meta
Thanks for sharing this. By far the best tool I've seen in the market centered around Code Integrity is CodiumAI (https://www.codium.ai/). They generate unit test based on entire code repos. Also integrates into SDLC through a PR Agent on GitHub or GitLab. My whole team uses them.
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What are some alternatives?
pynguin - The PYthoN General UnIt Test geNerator is a test-generation tool for Python
tunnelmole-client - Tunnelmole - Connect to local servers from anywhere
CrossHair - An analysis tool for Python that blurs the line between testing and type systems.
fuzz-introspector - Fuzz Introspector -- introspect, extend and optimise fuzzers
Polyester.jl - The cheapest threads you can find!
clang-contracts - Experimental support for contracts programming in clang++