Error Prone
MIRAI
Error Prone | MIRAI | |
---|---|---|
16 | 9 | |
6,724 | 960 | |
0.4% | 1.1% | |
9.4 | 0.0 | |
9 days ago | 4 months ago | |
Java | Rust | |
Apache License 2.0 | MIT License |
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.
Error Prone
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Any library you would like to recommend to others as it helps you a lot? For me, mapstruct is one of them. Hopefully I would hear some other nice libraries I never try.
error-prone is good for some extra static analysis.
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How to use Java Records
A special kind of validation is enforcing that record fields are not null. (Un)fortunately, records do not have any special behavior regarding nullability. You can use tools like NullAway or Error Prone to prevent null in your code in general, or you can add checks to your records:
- Prusti: Static Analyzer for Rust
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Why is `suspend` a language keyword, but @Composable and @Serializable are annotations
I am all in favour to more third side libraries adding functionalities, like Lombok, Manifold and error prone. As well as smaller projects like this shameless plug and what appears in this list
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Picnic loves Error Prone: producing high-quality and consistent Java code
If only Google didn't suck when it came to Java9+ support... https://github.com/google/error-prone/issues/2649
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What does the future hold for Project Amber?
I haven't used it. I use Google's ErrorProne + Lombok to prevent NPEs in java.
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Plans for Compile-time Null Pointer Safety?
Take a look at NullAway, a plugin for Error Prone.
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What I miss in Java, the perspective of a Kotlin developer
For some of this stuff, there are compiler extensions that allow extra type checking to be added e.g. Google Error-Prone: https://github.com/google/error-prone with stuff like: https://errorprone.info/bugpattern/ReturnMissingNullable.
Doesn't help you with third party libraries, but across an org applying that rule (and others!) typically ensures some consistency.
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A guide on how to improve your coding skills with static code analysis.
How to build a static analysis plugin. Google has a framework for Java with a good tutorial.
- Error Prone 2.11.0 Released. Requires JDK11+
MIRAI
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Is there something like "super-safe" rust?
MIRAI
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Adding “invariant” clauses to C++ via GCC plugin to enable Design-by-Contract
Do you use the Cargo "contracts" for Design-by-Contract style invariants that plugs into Facebook's MIRAI prover thing?
I always thought it this was super neat:
https://crates.io/crates/contracts
https://github.com/facebookexperimental/MIRAI/blob/main/exam...
[dependencies]
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Prusti: Static Analyzer for Rust
Here's a 2020 overview of Rust verification tools https://alastairreid.github.io/rust-verification-tools/ - it says
> Auto-active verification tools
> While automatic tools focus on things not going wrong, auto-active verification tools help you verify some key properties of your code: data structure invariants, the results of functions, etc. The price that you pay for this extra power is that you may have to assist the tool by adding function contracts (pre/post-conditions for functions), loop invariants, type invariants, etc. to your code.
> The only auto-active verification tool that I am aware of is Prusti. Prusti is a really interesting tool because it exploits Rust’s unusual type system to help it verify code. Also Prusti has the slickest user interface: a VSCode extension that checks your code as you type it!
> https://marketplace.visualstudio.com/items?itemName=viper-ad...
Now, on that list, there is also https://github.com/facebookexperimental/MIRAI that, alongside the crate https://crates.io/crates/contracts (with the mirai_assertion feature enabled) enables writing code like this
#[ensures(person_name.is_some() -> ret.contains(person_name.unwrap()))]
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Ten Years of TypeScript
Traditional design by contract checks the contracts at runtime. They can be understood as a form of dynamic typing with quite complicated types, which may be equivalent to refinement types
But you can check contracts at compile time too. It's quite the same thing as static typing with something like refinement types. That's because, while with contracts we can add preconditions like "the size of this array passed as parameter must be a prime number", with refinement types we can define the type of arrays whose size is a prime number, and then have this type as the function argument. (likewise, postconditions can be modeled by the return type of the function)
See for example this Rust library: https://docs.rs/contracts/latest/contracts/
It will by default check the contracts at runtime, but has an option to check them at compile time with https://github.com/facebookexperimental/MIRAI
Now, this Rust library isn't generally understood as creating another type system on top of Rust, but we could do the legwork to develop a type theory that models how it works, and show the equivalence.
Or, another example, Liquid Haskell: https://ucsd-progsys.github.io/liquidhaskell/ it implements a variant of refinement types called liquid types, which is essentially design by contract checked at compile type. In this case, the type theory is already developed. I expect Liquid Haskell to be roughly comparable to Rust's contracts checked by MIRAI.
Now, what we could perhaps say is that refinement types are so powerful that they don't feel like regular types! And, while that's true, there are type systems even more powerful: dependent types used in languages like Coq, Lean and F* to prove mathematical theorems (your type is a theorem, and your code, if it typechecks, is a proof of that theorem).
Dependent types were leveraged to create a verified TLS implementation that mathematically proves the absence of large class of bugs, miTLS https://www.mitls.org/ (they discovered a number of vulnerabilities in TLS implementations and proved that their implementation isn't vulnerable), and HACL* https://github.com/hacl-star/hacl-star a verified crypto implementation used by Firefox and Wireguard. They are part of Project Everest https://project-everest.github.io/ which aims to develop provably secure communications software.
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A pair of Linux kernel modules using Rust
Because it's convenient and familiar to most programmers. Not providing bounds-checked indexing makes some kinds of code very hard to write.
But note his problem also happens with integer division.
In Rust, a[x] on an array or vec is really a roughly a shortand for a.get(x).unwrap() (with a different error message)
Likewise, a / b on integers is a kind of a shortand for a.checked_div(b).unwrap()
The thing is, if the index ever is out of bounds, or if the denominator is zero, the program has a bug, 100% of time. And if you catch a bug using an assertion there is seldom anything better than interrupting the execution (the only thing I can think of is restarting the program or the subsystem). If you continue execution past a programming error, you may sometimes corrupt data structures or introduce bizarre, hard to debug situations.
Doing a pattern match on a.get(x) doesn't help because if it's ever None (and your program logic expects that x is in bounds) then you are kind of forced to bail.
The downside here is that we aren't catching this bug at compile time. And it's true that sometimes we can rewrite the program to not have an indexing operation, usually using iterators (eliding the bounds check will make the program run faster, too). But in general this is not possible, at least not without bringing formal methods. But that's what tests are for, to ensure the correctness of stuff type errors can't catch.
Now, there are some crates like https://github.com/dtolnay/no-panic or https://github.com/facebookexperimental/MIRAI that will check that your code is panic free. The first one is based on the fact that llvm optimizations can often remove dead code and thus remove the panic from a[x] or a / b - if it doesn't, then compilation fails. The second one employs formal methods to mathematically prove that there is no panic. I guess those techniques will eventually be ported to the kernel even if panics happen differently there (by hooking on the BUG mechanism or whatever)
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Does Rust not need extra linting and sanitizing tools like C++?
There's a MIR Abstract interpreter project: https://github.com/facebookexperimental/MIRAI
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Kani Rust Verifier – a bit-precise model-checker for Rust
Nice, I just would have liked to get all these different verification tools combined under the same interface, just being different backends as drafted by the rust verification tools work of project oak: have "cargo verify" as common command and use common test annotations, allowing the same test to be verified with different backends or just fuzzed/proptested.
The model checking approach seems to be a bit limited regarding loops. There are also abstract interpreters, such as https://github.com/facebookexperimental/MIRAI, and symbolic executers, such as https://github.com/dwrensha/seer or https://github.com/GaloisInc/crucible.
Overall I believe this space would benefit from more coordination and focus on developing something that has the theoretical foundations to cover as many needs as possible and then make a user-friendly tool out of it that is endorsed by the Rust project similar to how Rust analyzer is the one language server to come.
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Things I hate about Rust, redux
https://github.com/facebookexperimental/MIRAI which integrates with https://crates.io/crates/contracts (a crate that does runtime checking of contracts, and with mirai they are upgraded to compile-time checking) and https://crates.io/crates/mirai-annotations
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Is Rust Used Safely by Software Developers?
With the mirai_assertions feature, it can use the MIRAI static analyzer (though it requires nightly).
What are some alternatives?
Spotbugs - SpotBugs is FindBugs' successor. A tool for static analysis to look for bugs in Java code.
rust-on-raspberry-pi
SonarQube - Continuous Inspection
prusti-dev - A static verifier for Rust, based on the Viper verification infrastructure.
PMD - An extensible multilanguage static code analyzer.
rust-mode - Emacs configuration for Rust
Checkstyle - Checkstyle is a development tool to help programmers write Java code that adheres to a coding standard. By default it supports the Google Java Style Guide and Sun Code Conventions, but is highly configurable. It can be invoked with an ANT task and a command line program.
kani - Kani Rust Verifier
FindBugs - The new home of the FindBugs project
just - 🤖 Just a command runner
infer - A static analyzer for Java, C, C++, and Objective-C
Rustup - The Rust toolchain installer