Rust’s concurrency model leverages its ownership and borrowing rules to guarantee thread safety at compile time, eliminating data races without requiring a garbage collector. This approach ensures safe, high-performance parallelism with minimal runtime overhead.

Rust’s Concurrency Model

Rust uses the following mechanisms to manage concurrency:

Ownership: Ensures exclusive mutable access to data.
Borrowing: Governs how data is accessed via references.
Lifetimes: Prevent dangling references across threads.
Send/Sync Traits: Define which types are safe for threading.

How Ownership and Borrowing Prevent Data Races

A data race occurs when:

Two threads access the same data concurrently.
At least one access is a write.
There’s no synchronization.

Rust’s rules make data races impossible in safe code:

1. Exclusive Mutability (`&mut T`)

Only one mutable reference (&mut T) can exist at a time, enforced by the borrow checker.
This prevents multiple threads from writing to the same data simultaneously.

Example:

let mut data = 0;
let r1 = &mut data;  // OK: Mutable borrow
// let r2 = &mut data;  // ERROR: Cannot borrow `data` as mutable more than once

2. No Shared Mutability Without Synchronization

Shared references (&T) are read-only, safe for concurrent access.
To mutate shared data, synchronization primitives like Mutex are required:

Example:

use std::sync::Mutex;

let shared = Mutex::new(42);
let guard = shared.lock().unwrap();  // Exclusive access
*guard += 1;  // Safe mutation

Thread-Safe Types: Send and Sync

Send: A type can be safely transferred across threads (e.g., String, Mutex<T>).
Sync: A type can be safely shared between threads via references (e.g., &i32, Arc<T>).

Example: Spawning Threads:

use std::thread;

let value = String::from("hello");  // `String` is `Send`
thread::spawn(move || {             // `move` transfers ownership
    println!("{}", value);          // Safe: no other thread can access `value`
}).join().unwrap();

Common Concurrency Tools

Tool	Purpose	Thread Safety Mechanism
`Mutex<T>`	Mutual exclusion	Locks for exclusive access
`Arc<T>`	Atomic reference counting	Shared ownership across threads
`RwLock<T>`	Read-write lock	Multiple readers or one writer
`mpsc channels`	Message passing	Transfers ownership between threads

Example: Shared State with Arc + Mutex:

use std::sync::{Arc, Mutex};
use std::thread;

let counter = Arc::new(Mutex::new(0));
let mut handles = vec![];

for _ in 0..10 {
    let counter = Arc::clone(&counter);
    handles.push(thread::spawn(move || {
        let mut num = counter.lock().unwrap();
        *num += 1;  // Mutex ensures exclusive access
    }));
}

for handle in handles {
    handle.join().unwrap();
}
println!("Result: {}", *counter.lock().unwrap());  // Outputs 10

Why This Matters

No runtime overhead: Safety checks occur at compile time.
No garbage collector: Safe concurrency without GC pauses.
Fearless parallelism: The compiler rejects unsafe patterns, enabling confident concurrent programming.

Key Takeaways

✅ Ownership rules prevent:

Concurrent mutable access (no data races).
Dangling references (via lifetimes).

✅ Send/Sync enforce thread safety at compile time.

🚀 Use Mutex, Arc, or channels for safe shared state.

Real-World Impact: Crates like rayon (parallel iterators) and tokio (async runtime) rely on these guarantees for robust concurrency.

Experiment: What happens if you try to share an Rc<T> across threads?
Answer: Compile error! Rc<T> is not Send (not thread-safe). Use Arc<T> instead.

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