Rust vs. C++: 6 Key Differences and Pros and Cons for Programming With Each

Comparing Rust and C++ – A Guide for Systems Programmers

As a developer looking to build a new application, you may be evaluating Rust and C++ – two programming languages built specifically for systems development. Both offer excellent performance and control over hardware resources needed for system software and infrastructure.

However, Rust and C++ take fundamentally different approaches in areas like memory safety, concurrency, tooling and syntax. Understanding their trade-offs is key before adopting one language or the other. This comprehensive guide examines factors you should consider when deciding between Rust and C++.

Key Differences at a Glance

Diving Deep into Memory Safety Approaches

Memory bugs have historically been a source of crashes, security issues and headache for programmers. Languages tackle this problem through different means.

Rust‘s novel ownership concept enforces rules about object lifetimes and mutable access. By preventing dangling pointers, double frees and data races in safe Rust, entire classes of memory issues are eliminated. The compiler guarantees this before code even runs. For example, NULL deference bugs which make up over 25% of all High and Critical defects in C/C++ are impossible in Rust.

C++ leaves responsibility to manage memory manually using new, delete and smart pointers. Skilled programmers apply patterns like RAII effectively. However, the poka-yoke model of Rust prevents mistakes by design. Studies have found over 5x fewer memory safety bugs in Rust code than C++.

Let‘s examine this difference with an example:

// C++

void process(Data* input) {
  Data output;
  // use input and output
} // output destroyed

// Rust 

fn process(input: &Data) -> Data {
   let output = Data::new(); // created
   // use input and output
   output // returned 
} // output dropped

Rust moves allocation and de-allocation automatically to the scopes where they make most sense. The compiler infers lifetimes, freeing you from manually thinking about these aspects.

Concurrency and Parallelism Support

Modern system scale by running work concurrently across threads and cores. But shared data access needs coordination to avoid race conditions.

Rust‘s ownership model prevents data races at compile-time allowing fearless concurrency between threads without overhead. Safe abstractions like message passing channels and atomic data types facilitate concurrent coding.

C++ relies on libraries like Boost and language extensions to enable patterns like mutexes for coordinating threads. However, program correctness depends on developers applying these patterns properly everywhere shared state is accessed…

Appendix A – Pros and Cons Summary