The Detroit Post
Thursday, 21 October, 2021

How Does Rust Prevent Data Races

Maria Garcia
• Friday, 23 October, 2020
• 7 min read

A data race has Undefined Behavior, and is therefore impossible to perform in Safe Rust. Any system that could genuinely claim to prevent all race conditions would be pretty awful to use, if not just incorrect.

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So it's perfectly “fine” for a Safe Rust program to get deadlocked or do something nonsensical with incorrect synchronization. Still, a race condition can't violate memory safety in a Rust program on its own.

Making statements based on opinion; back them up with references or personal experience. Then maybe your points make some sense but it is exactly the code handling these that I am saying does not fit with what I have seen rust advocates claim.

Its actual guarantees for atomic are not very strong and let you handle all of those things in safe code. The implementations of those things are still unsafe, but you can generally provide a safe API to them, which you can't do in most other languages.

This is because Rust has the notion of thread safety built into the language and enforced by the type system. That doesn't mean you can't build up a safe type from the lower level atomic, or Rust isn't suited for this domain.

> You have to reason about these things at some level, and what I hear people advocate on in is to sidestep it all by preventing sharing, which may be a fine idea but doesn't work for everything. But data races in general can produce corrupt values that are invalid for a type (type unsafe) when the object being raced for spans multiple words, and/or produce values that point to invalid memory locations (memory unsafe) when pointers are involved.

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Initially these problems seemed orthogonal, but to our amazement, the solution turned out to be identical: the same tools that make Rust safe also help you tackle concurrency head-on. For memory safety, this means you can program without a garbage collector and without fear of segfaults, because Rust will catch your mistakes.

For concurrency, this means you can choose from a wide variety of paradigms (message passing, shared state, lock-free, purely functional), and Rust will help you avoid common pitfalls. Even the most daring forms of sharing are guaranteed safe in Rust.

All of these benefits come out of Rust's ownership model, and in fact locks, channels, lock-free data structures and so on are defined in libraries, not the core language. That means that Rust's approach to concurrency is open-ended : new libraries can embrace new paradigms and catch new bugs, just by adding APIs that use Rust's ownership features.

We'll start with an overview of Rust's ownership and borrowing systems. If you're already familiar with these, you can skip the two “background” sections and jump straight into concurrency.

If you want a deeper introduction, I can't recommend Neruda Katz's post highly enough. Values that are still owned when a scope ends are automatically destroyed at that point.

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On the other hand, the print_vec function takes a DEC parameter, and ownership of the vector is transferred to it by its caller. Rust will check that these leases do not outlive the object being borrowed.

To borrow a value, you make a reference to it (a kind of pointer), using the & operator: Since borrows are temporary, use_vec retains ownership of the vector; it can continue using it after the call to print_vec returns (and its lease on DEC has expired).

Each reference is valid for a limited scope, which the compiler will automatically determine. Rust checks these rules at compile time; borrowing has no runtime overhead.

The iterator keeps a pointer into the vector at the current and final positions, stepping one toward the other. Now that we've covered the basic ownership story in Rust, let's see what it means for concurrency.

Channels are generic over the type of data they transmit (the part of the API). As always in Rust, passing in a T to the send function means transferring ownership of it.

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Another way to deal with concurrency is by having threads communicate through passive, shared state. It's easy to forget to acquire a lock, or otherwise mutate the wrong data at the wrong time, with disastrous results -- so easy that many eschew the style altogether.

Rust aims to give you the tools to conquer shared-state concurrency directly, whether you're using locking or lock-free techniques. In Rust, threads are “isolated” from each other automatically, due to ownership.

Locks provide the same guarantee (“mutual exclusion”) through synchronization at runtime. That leads to a locking API that hooks directly into Rust's ownership system.

The Mudguard automatically releases the lock when it is destroyed; there is no separate unlock function. The mutable reference returned by access cannot outlive the Mudguard it is borrowing from.

For example, Rust ships with two kinds of “smart pointers” for reference counting: On the other hand, it's critical that a RC never migrate from one thread to another, because that could lead to race conditions that corrupt the count.

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Usually, the only recourse is careful documentation; most languages make no semantic distinction between thread-safe and thread-unsafe types. In Rust, the world is divided into two kinds of data types: those that are Send, meaning they can be safely moved from one thread to another, and those that are ! Send, meaning that it may not be safe to do so.

Putting this all together, Rust programmers can reap the benefits of RC and other thread- unsafe types with confidence, knowing that if they ever do accidentally try to send one to another thread, the Rust compiler will say: So far, all the patterns we've seen involve creating data structures on the heap that get shared between threads.

But what if we wanted to start some threads that make use of data living in our stack frame? The child thread takes a reference to DEC, which in turn resides in the stack frame of parent.

It means that a function like parent above will generate an error: Essentially catching the possibility of parent's stack frame popping.

Thus, by adjusting our previous example, we can fix the bug and satisfy the compiler: So in Rust, you can freely borrow stack data into child threads, confident that the compiler will check for sufficient synchronization.


At this point, we've seen enough to venture a strong statement about Rust's approach to concurrency: the compiler prevents all data races. It's worth pausing for a moment to think about this guarantee in the broader landscape of languages.

Many languages provide memory safety through garbage collection. But garbage collection doesn't give you any help in preventing data races.

Rust instead uses ownership and borrowing to provide its two key value propositions: When Rust first began, it baked channels directly into the language, taking a very opinionated stance on concurrency.

And that's very exciting, because it means that Rust's concurrency story can endlessly evolve, growing to encompass new paradigms and catch new classes of bugs. Libraries like sync box and simple_parallel are taking some first steps, and we expect to invest heavily in this space in the next few months.

Press question mark to learn the rest of the keyboard shortcuts In Rust everything is compiled checked, the best, and in Go we have runtime detection, which is way better than the rest of the market.

One of few ways to really boost a new programming language is to have some “killer app,” something people really, really want to do with it. But for that to happen, some effort must me expended to make the experience as good as possible and as noob-friendly as possible (within reason, of course).

I don't think it would take that much time for someone who already knows how everything is supposed to work to set things up, but that would greatly benefit many beginners. Unlike other libraries, desert is not bound to any data format because it does not perform parsing.

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