CrossHair
practical-fm
CrossHair | practical-fm | |
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8 | 4 | |
948 | 461 | |
- | - | |
9.2 | 4.1 | |
11 days ago | about 1 month ago | |
Python | ||
GNU General Public License v3.0 or later | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CrossHair
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Try CrossHair while working other Python projects
Writing some Python for Hacktoberfest? Try out CrossHair while you do that and get credit for a blog post too! https://github.com/pschanely/CrossHair/issues/173
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What are some amazing, great python external modules, libraries to explore?
CrossHair, Hypothesis, and Mutmut for advanced testing.
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Formal Verification Methods in industry
When you say "formal verification methods", what kind of techniques are you interested in? While using interactive theorem provers will most likely not become very widespread, there are plenty of tools that use formal techniques to give more correctness guarantees. These tools might give some guarantees, but do not guarantee complete functional correctness. WireGuard (VPN tunnel) is I think a very interesting application where they verified the protocol. There are also some tools in use, e.g. Mythril and CrossHair, that focus on detecting bugs using symbolic execution. There's also INFER from Facebook/Meta which tries to verify memory safety automatically. The following GitHub repo might also interest you, it lists some companies that use formal methods: practical-fm
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Klara: Python automatic test generations and static analysis library
The main difference that Klara bring to the table, compared to similar tool like pynguin and Crosshair is that the analysis is entirely static, meaning that no user code will be executed, and you can easily extend the test generation strategy via plugin loading (e.g. the options arg to the Component object returned from function above is not needed for test coverage).
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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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Programming in Z3 by learning to think like a compiler
There's a tool for verification of Python programs based on contracts which uses Z3: https://github.com/pschanely/CrossHair
You can use it as part of your CI or during the development (there's even a neat "watch" mode, akin to auto-correct).
- Diff the behavior of two Python functions
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Finding Software Bugs Using Symbolic Execution
Looking at some of your SMT-based projects, I'd love to compare your SMT solver notes with my mine from working on https://github.com/pschanely/CrossHair
Sadly, there aren't a lot of resources on how to use SMT solvers well.
practical-fm
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We Need Simpler Types (speculations on what can be improved in future type systems and on erasing the boundaries between types and values)
https://github.com/ligurio/practical-fm Look for Coq, Agda, Idris, MS - F*.
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Interested in pursuing a PhD in Formal Methods
Does your current company have FM positions? Maybe you could work and learn at the same time. There are a lot of big name companies that are really investing in FM now that more tools are available. Here’s a list someone compiled that can give you an idea of where it’s being used in industry. I see some info is not quite up-to-date (e.g., IBM does have FM, or formal verification, in the US but I think most research is out of their Israel lab; Rockwell Collins is now Collins Aerospace after being acquired by UTC Aerospace).
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Formal Verification Methods in industry
When you say "formal verification methods", what kind of techniques are you interested in? While using interactive theorem provers will most likely not become very widespread, there are plenty of tools that use formal techniques to give more correctness guarantees. These tools might give some guarantees, but do not guarantee complete functional correctness. WireGuard (VPN tunnel) is I think a very interesting application where they verified the protocol. There are also some tools in use, e.g. Mythril and CrossHair, that focus on detecting bugs using symbolic execution. There's also INFER from Facebook/Meta which tries to verify memory safety automatically. The following GitHub repo might also interest you, it lists some companies that use formal methods: practical-fm
- A list of companies that use formal verification methods
What are some alternatives?
pynguin - The PYthoN General UnIt Test geNerator is a test-generation tool for Python
magmide - A dependently-typed proof language intended to make provably correct bare metal code possible for working software engineers.
icontract-hypothesis - Combine contracts and automatic testing.
ouroboros-high-assurance - High-assurance implementation of the Ouroboros protocol family
angr - A powerful and user-friendly binary analysis platform!
CommunityModules - TLA+ snippets, operators, and modules contributed and curated by the TLA+ community
alive2 - Automatic verification of LLVM optimizations
hacl-star - HACL*, a formally verified cryptographic library written in F*
klee - KLEE Symbolic Execution Engine
silveroak - Formal specification and verification of hardware, especially for security and privacy.
miasm - Reverse engineering framework in Python
timewinder - Temporal Logic of Actions in Rust via Starlark