While I was busy doing Rust-unrelated research, RustBelt continues to move and recently found another bug (after a missing
impl !Sync that we found previously): It turns out that
Arc::get_mut did not perform sufficient synchronization, leading to a data race.
Notice that I am just the messenger here, the bug was actually found by Hai and Jacques-Henri. Still, I’d like to use this opportunity to talk a bit about weak memory, synchronization and data races. This is just a primer, there are tons of resources on the web that go into more detail (for example here).
In my last post, I talked about the new “pinned references” which guarantee that the data at the memory it points to will not, ever, be moved elsewhere.
I explained how they enable giving a safe API to code that could previously only be exposed with
unsafe, and how one could go about proving such a thing.
This post is about another application of pinned references—another API whose safety relies on the pinning guarantees: Intrusive collections.
It turns out that pinned references can almost be used for this, but not quite.
However, this can be fixed by extending the guarantees provided by pinned references, as suggested by @cramertj.
Recently, a new API for “pinned references” has landed as a new unstable feature in the standard library. The purpose of these references is to express that the data at the memory it points to will not, ever, be moved elsewhere. @withoutboats has written about how this solves a problem in the context of async IO. In this post, we take a closer, more formal look at that API: We are going to take a stab at extending the RustBelt model of types with support for pinning.
This post is about an aspect of the RustBelt paper. Concretely, I’d like to share some of our thoughts on the nature of types and shared references. Let’s see how well this goes. :)
Shared references are an extremely powerful mechanism in the Rust type system, and we’ve had quite some trouble finding a good way of handling them in our formal model. In this post, I will present the model that we came up with.
Last week, I was in Los Angeles at POPL 2018 to present our paper RustBelt: Securing the Foundations of the Rust Programming Language. The talk has been recorded, so if you want to get a 20-minute summary of the paper, go watch it on YouTube. If you have any questions, feel free to join the forum thread linked below :)
POPL 2018, the conference where I will present our RustBelt paper, is doing a series of interviews with senior and junior people from the community: People of Programming Languages. They also asked me if I wanted to be part of this, and of course I accepted. This was the first time I was asked to give an interview, so needless to say, I was super excited! I got the opportunity to talk about how I came to do research in PL, what my research is about, and ramble a bit about why I think Coq is great. If you want to read more, check out my interview. Be sure to also have a look at the other interviews.
Thanks a lot to Jean Yang, the Publicity Chair for POPL 2018, for making this a very pleasant experience. (Though, as you can see, I had to send them a picture, which was certainly the least pleasant part of this. ;)
PS: It seems I have consistent bad luck with my POPL talk slots, because my talk is again in the very last session of the conference. This time, in fact, it’s the very last talk of the main track. Maybe some people read this interview and consider staying anyway :D
Just yesterday, we submitted our paper RustBelt: Securing the Foundations of the Rust Programming Language. Quoting from the abstract:
Rust is a new systems programming language that promises to overcome the seemingly fundamental tradeoff between high-level safety guarantees and low-level control over resource management. Unfortunately, none of Rust’s safety claims have been formally proven, and there is good reason to question whether they actually hold. Specifically, Rust employs a strong, ownership-based type system, but then extends the expressive power of this core type system through libraries that internally use unsafe features. In this paper, we give the first formal (and machine-checked) safety proof for a language representing a realistic subset of Rust. Our proof is extensible in the sense that, for each new Rust library that uses unsafe features, we can say what verification condition it must satisfy in order for it to be deemed a safe extension to the language. We have carried out this verification for some of the most important libraries that are used throughout the Rust ecosystem.
A couple of weeks ago, our ongoing effort to formalize Rust’s type system lead to us actually discovering a bug in the Rust standard library:
Sync in cases where it should not. This could lead to data races in safe programs. Ouch.
This week, I have been at the Paris Rust Meetup. Meeting all sorts of Rust people was great fun, and the Mozilla offices in Paris are absolutely impressive. You should totally check them out if you have a chance.
On that meetup, I gave a short talk about the current status of my formalization of the Rust type system.
I’d like to talk about an important aspect of dealing with unsafe code, that still regularly seems to catch people on the wrong foot:
When checking unsafe code, it is not enough to just check the contents of every
The “scope” in the title refers to the extent of the code that has to be manually checked for correctness, once
unsafe is used.
What I am saying is that the scope of
unsafe is larger than the
unsafe block itself.
It turns out that the underlying reason for this observation is also a nice illustration for the concept of semantic types that comes up in my work on formalizing Rust (or rather, its type system). Finally, this discussion will once again lead us to realize that we rely on our type systems to provide much more than just type safety.
Update (Jan 11th): Clarified the role of privacy; argued why
evil is the problem.
My current research project – and the main topic of my PhD thesis – is about developing a semantic model of the Rust programming language and, most importantly, its type system. Rust is an attempt of Mozilla to find a sweet spot in the design space of programming languages: A language that provides low-level resource management (making it a systems language), is convenient for programmers and guards against memory errors and thread unsafety. Other have said and written a lot on why we need such a language, so I won’t lose any more words on this. Let me just use this opportunity for a shameless plug: If you are curious and want to learn Rust, check out Rust-101, a hands-on Rust tutorial I wrote. I am going to assume some basic familiarity with Rust in the following.
Why do we want to do research on Rust? First of all, I’m (becoming) a programming languages researcher, and Rust is an interesting new language to study. It’s going to be fun! Honestly, that’s enough of a reason for me. But there are other reasons: It shouldn’t be a surprise that bugs have been found in Rust. There are lots of things that can be done about such bugs – my take on this is that we should try to prove, in a mathematical rigorous way, that no such bugs exist in Rust. This goes hand-in-hand with other approaches like testing, fuzzing and static analysis. However, we (at my research group) are into formalizing things, so that’s what we are going to do as part of the RustBelt research project.
Update: Added link to RustBelt website.