One of the main challenges of evaluating Rust for use within the Android platform was ensuring we could provide sufficient interoperability with our existing codebase. If Rust is to meet its goals of improving security, stability, and quality Android-wide, we need to be able to use Rust anywhere in the codebase that native code is required. To accomplish this, we need to provide the majority of functionality platform developers use. As we discussed previously, we have too much C++ to consider ignoring it, rewriting all of it is infeasible, and rewriting older code would likely be counterproductive as the bugs in that code have largely been fixed. This means interoperability is the most practical way forward.
Before introducing Rust into the Android Open Source Project (AOSP), we needed to demonstrate that Rust interoperability with C and C++ is sufficient for practical, convenient, and safe use within Android. Adding a new language has costs; we needed to demonstrate that Rust would be able to scale across the codebase and meet its potential in order to justify those costs. This post will cover the analysis we did more than a year ago while we evaluated Rust for use in Android. We also present a follow-up analysis with some insights into how the original analysis has held up as Android projects have adopted Rust.
Existing language interoperability in Android focuses on well defined foreign-function interface (FFI) boundaries, which is where code written in one programming language calls into code written in a different language. Rust support will likewise focus on the FFI boundary as this is consistent with how AOSP projects are developed, how code is shared, and how dependencies are managed. For Rust interoperability with C, the C application binary interface (ABI) is already sufficient.
Interoperability with C++ is more challenging and is the focus of this post. While both Rust and C++ support using the C ABI, it is not sufficient for idiomatic usage of either language. Simply enumerating the features of each language results in an unsurprising conclusion: many concepts are not easily translatable, nor do we necessarily want them to be. After all, we’re introducing Rust because many features and characteristics of C++ make it difficult to write safe and correct code. Therefore, our goal is not to consider all language features, but rather to analyze how Android uses C++ and ensure that interop is convenient for the vast majority of our use cases.
We analyzed code and interfaces in the Android platform specifically, not codebases in general. While this means our specific conclusions may not be accurate for other codebases, we hope the methodology can help others to make a more informed decision about introducing Rust into their large codebase. Our colleagues on the Chrome browser team have done a similar analysis, which you can find here.
This analysis was not originally intended to be published outside of Google: our goal was to make a data-driven decision on whether or not Rust was a good choice for systems development in Android. While the analysis is intended to be accurate and actionable, it was never intended to be comprehensive, and we’ve pointed out a couple of areas where it could be more complete. However, we also note that initial investigations into these areas showed that they would not significantly impact the results, which is why we decided to not invest the additional effort.
Exported functions from Rust and C++ libraries are where we consider interop to be essential. Our goals are simple:
While making Rust functions callable from C++ is a goal, this analysis focuses on making C++ functions available to Rust so that new Rust code can be added while taking advantage of existing implementations in C++. To that end, we look at exported C++ functions and consider existing and planned compatibility with Rust via the C ABI and compatibility libraries. Types are extracted by running objdump on shared libraries to find external C++ functions they use1 and running c++filt to parse the C++ types. This gives functions and their arguments. It does not consider return values, but a preliminary analysis2 of those revealed that they would not significantly affect the results.
objdump
c++filt
We then classify each of these types into one of the following buckets:
These are generally simple types involving primitives (including pointers and references to them). For these types, Rust’s existing FFI will handle them correctly, and Android’s build system will auto-generate the bindings.
These are handled by the cxx crate. This currently includes std::string, std::vector, and C++ methods (including pointers/references to these types). Users simply have to define the types and functions they want to share across languages and cxx will generate the code to do that safely.
std::string
std::vector,
These types are not directly supported, but the interfaces that use them have been manually reworked to add Rust support. Specifically, this includes types used by AIDL and protobufs.
We have also implemented a native interface for StatsD as the existing C++ interface relies on method overloading, which is not well supported by bindgen and cxx3. Usage of this system does not show up in the analysis because the C++ API does not use any unique types.
This is currently common data structures such as std::optional and std::chrono::duration and custom string and vector implementations.
std::optional
std::chrono::duration
These can either be supported natively by a future contribution to cxx, or by using its ExternType facilities. We have only included types in this category that we believe are relatively straightforward to implement and have a reasonable chance of being accepted into the cxx project.
Some types are exposed in today’s C++ APIs that are either an implicit part of the API, not an API we expect to want to use from Rust, or are language specific. Examples of types we do not intend to support include:
native_handle
std::locale&
cout
Overall, this category represents types that we do not believe a Rust developer should be using.
Android is in the process of deprecating HIDL and migrating to AIDL for HALs for new services.We’re also migrating some existing implementations to stable AIDL. Our current plan is to not support HIDL, preferring to migrate to stable AIDL instead. These types thus currently fall into the “We don't need/intend to support'' bucket above, but we break them out to be more specific. If there is sufficient demand for HIDL support, we may revisit this decision later.
This contains all types that do not fit into any of the above buckets. It is currently mostly std::string being passed by value, which is not supported by cxx.
One of the primary reasons for supporting interop is to allow reuse of existing code. With this in mind, we determined the most commonly used C++ libraries in Android: liblog, libbase, libutils, libcutils, libhidlbase, libbinder, libhardware, libz, libcrypto, and libui. We then analyzed all of the external C++ functions used by these libraries and their arguments to determine how well they would interoperate with Rust.
liblog
libbase
libutils
libcutils
libhidlbase
libbinder
libhardware
libz
libcrypto
libui
Overall, 81% of types are in the first three categories (which we currently fully support) and 87% are in the first four categories (which includes those we believe we can easily support). Almost all of the remaining types are those we believe we do not need to support.
In addition to analyzing popular C++ libraries, we also examined Mainline modules. Supporting this context is critical as Android is migrating some of its core functionality to Mainline, including much of the native code we hope to augment with Rust. Additionally, their modularity presents an opportunity for interop support.
We analyzed 64 binaries and libraries in 21 modules. For each analyzed library we examined their used C++ functions and analyzed the types of their arguments to determine how well they would interoperate with Rust in the same way we did above for the top 10 libraries.
Here 88% of types are in the first three categories and 90% in the first four, with almost all of the remaining being types we do not need to handle.
With almost a year of Rust development in AOSP behind us, and more than a hundred thousand lines of code written in Rust, we can now examine how our original analysis has held up based on how C/C++ code is currently called from Rust in AOSP.4
The results largely match what we expected from our analysis with bindgen handling the majority of interop needs. Extensive use of AIDL by the new Keystore2 service results in the primary difference between our original analysis and actual Rust usage in the “Native Support” category.
A few current examples of interop are:
Bindgen and cxx provide the vast majority of Rust/C++ interoperability needed by Android. For some of the exceptions, such as AIDL, the native version provides convenient interop between Rust and other languages. Manually written wrappers can be used to handle the few remaining types and functions not supported by other options as well as to create ergonomic Rust APIs. Overall, we believe interoperability between Rust and C++ is already largely sufficient for convenient use of Rust within Android.
If you are considering how Rust could integrate into your C++ project, we recommend doing a similar analysis of your codebase. When addressing interop gaps, we recommend that you consider upstreaming support to existing compat libraries like cxx.
Our first attempt at quantifying Rust/C++ interop involved analyzing the potential mismatches between the languages. This led to a lot of interesting information, but was difficult to draw actionable conclusions from. Rather than enumerating all the potential places where interop could occur, Stephen Hines suggested that we instead consider how code is currently shared between C/C++ projects as a reasonable proxy for where we’ll also likely want interop for Rust. This provided us with actionable information that was straightforward to prioritize and implement. Looking back, the data from our real-world Rust usage has reinforced that the initial methodology was sound. Thanks Stephen!Also, thanks to:
We used undefined symbols of function type as reported by objdump to perform this analysis. This means that any header-only functions will be absent from our analysis, and internal (non-API) functions which are called by header-only functions may appear in it. ↩
We extracted return values by parsing DWARF symbols, which give the return types of functions. ↩
Even without automated binding generation, manually implementing the bindings is straightforward. ↩
In the case of handwritten C/C++ wrappers, we analyzed the functions they call, not the wrappers themselves. For all uses of our native AIDL library, we analyzed the types used in the C++ version of the library. ↩
The Android team has been working on introducing the Rust programming language into the Android Open Source Project (AOSP) since 2019 as a memory-safe alternative for platform native code development. As with any large project, introducing a new language requires careful consideration. For Android, one important area was assessing how to best fit Rust into Android’s build system. Currently this means the Soong build system (where the Rust support resides), but these design decisions and considerations are equally applicable for Bazel when AOSP migrates to that build system. This post discusses some of the key design considerations and resulting decisions we made in integrating Rust support into Android’s build system.
A RustConf 2019 meeting on Rust usage within large organizations highlighted several challenges, such as the risk that eschewing Cargo in favor of using the Rust Compiler, rustc, directly (see next section) may remove organizations from the wider Rust community. We share this same concern. When changes to imported third-party crates might be beneficial to the wider community, our goal is to upstream those changes. Likewise when crates developed for Android could benefit the wider Rust community, we hope to release them as independent crates. We believe that the success of Rust within Android is dependent on minimizing any divergence between Android and the Rust community at large, and hope that the Rust community will benefit from Android’s involvement.
rustc,
Rust provides Cargo as the default build system and package manager, collecting dependencies and invoking rustc (the Rust compiler) to build the target crate (Rust package). Soong takes this role instead in Android and calls rustc directly for several reasons:
rustc
Cargo.toml
build.rs
Using the Rust compiler directly allows us to avoid these issues and is consistent with how we compile all other code in AOSP. It provides the most control over the build process and eases integration into Android’s existing build system. Unfortunately, avoiding it introduces several challenges and influences many other build system decisions because Cargo usage is so deeply ingrained in the Rust crate ecosystem.
A build.rs script compiles to a Rust binary which Cargo builds and executes during a build to handle pre-build tasks, commonly setting up the build environment, or building libraries in other languages (for example C/C++). This is analogous to configure scripts used for other languages.
Avoiding build.rs scripts somewhat flows naturally from not relying on Cargo since supporting these would require replicating Cargo behavior and assumptions. Beyond this however, there are good reasons for AOSP to avoid build scripts as well:
/usr/lib
Android.bp
For instances in third-party code where a build script is used only to compile C dependencies, we either use existing cc_library Soong definitions (such as boringssl for quiche) or create new definitions for crate-specific code.
cc_library
When the build.rs is used to generate source, we try to replicate the core functionality in a Soong rust_binary module for use as a custom source generator. In other cases where Soong can provide the information without source generation, we may carry a small patch that leverages this information.
Why do we support proc_macros, which are compiler plug-ins that execute code on the host within the compiler context, but not build.rs scripts?
proc_macros
While build.rs code is written as one-off code to handle building a single crate, proc_macros define reusable functionality within the compiler which can become widely relied upon across the Rust community. As a result popular proc_macros are generally better maintained and more scrutinized upstream, which makes the code review process more manageable. They are also more readily sandboxed as part of the build process since they are less likely to have dependencies external to the compiler.
proc_macros are also a language feature rather than a method for building code. These are relied upon by source code, are unavoidable for third-party dependencies, and are useful enough to define and use within our platform code. While we can avoid build.rs by leveraging our build system, the same can’t be said of proc_macros.
There is also precedence for compiler plugin support within the Android build system. For example see Soong’s java_plugin modules.
Unlike C/C++ compilers, rustc only accepts a single source file representing an entry point to a binary or library. It expects that the source tree is structured such that all required source files can be automatically discovered. This means that generated source either needs to be placed in the source tree or provided through an include directive in source:
include!("/path/to/hello.rs");
The Rust community depends on build.rs scripts alongside assumptions about the Cargo build environment to get around this limitation. When building, the cargo command sets an OUT_DIR environment variable which build.rs scripts are expected to place generated source code in. This source can then be included via:
cargo
include!(concat!(env!("OUT_DIR"), "/hello.rs"));
This presents a challenge for Soong as outputs for each module are placed in their own out/ directory2; there is no single OUT_DIR where dependencies output their generated source.
out/
OUT_DIR
For platform code, we prefer to package generated source into a crate that can be imported. There are a few reasons to favor this approach:
As a result, all of Android’s Rust source generation module types produce code that can be compiled and used as a crate.
We still support third-party crates without modification by copying all the generated source dependencies for a module into a single per-module directory similar to Cargo. Soong then sets the OUT_DIR environment variable to that directory when compiling the module so the generated source can be found. However we discourage use of this mechanism in platform code unless absolutely necessary for the reasons described above.
By default, the Rust ecosystem assumes that crates will be statically linked into binaries. The usual benefits of dynamic libraries are upgrades (whether for security or functionality) and decreased memory usage. Rust’s lack of a stable binary interface and usage of cross-crate information flow prevents upgrading libraries without upgrading all dependent code. Even when the same crate is used by two different programs on the system, it is unlikely to be provided by the same shared object4 due to the precision with which Rust identifies its crates. This makes Rust binaries more portable but also results in larger disk and memory footprints.
This is problematic for Android devices where resources like memory and disk usage must be carefully managed because statically linking all crates into Rust binaries would result in excessive code duplication (especially in the standard library). However, our situation is also different from the standard host environment: we build Android using global decisions about dependencies. This means that nearly every crate is shareable between all users of that crate. Thus, we opt to link crates dynamically by default for device targets. This reduces the overall memory footprint of Rust in Android by allowing crates to be reused across multiple binaries which depend on them.
Since this is unusual in the Rust community, not all third-party crates support dynamic compilation. Sometimes we must carry small patches while we work with upstream maintainers to add support.
We support building all output types supported by rustc (rlibs, dylibs, proc_macros, cdylibs, staticlibs, and executables). Rust modules can automatically request the appropriate crate linkage for a given dependency (rlib vs dylib). C and C++ modules can depend on Rust cdylib or staticlib producing modules the same way as they would for a C or C++ library.
rlib
dylib
proc_macro
cdylib
staticlib
In addition to being able to build Rust code, Android’s build system also provides support for protobuf and gRPC and AIDL generated crates. First-class bindgen support makes interfacing with existing C code simple and we have support modules using cxx for tighter integration with C++ code.
The Rust community produces great tooling for developers, such as the language server rust-analyzer. We have integrated support for rust-analyzer into the build system so that any IDE which supports it can provide code completion and goto definitions for Android modules.
Source-based code coverage builds are supported to provide platform developers high level signals on how well their code is covered by tests. Benchmarks are supported as their own module type, leveraging the criterion crate to provide performance metrics. In order to maintain a consistent style and level of code quality, a default set of clippy lints and rustc lints are enabled by default. Additionally, HWASAN/ASAN fuzzers are supported, with the HWASAN rustc support added to upstream.
clippy
In the near future, we plan to add documentation to source.android.com on how to define and use Rust modules in Soong. We expect Android’s support for Rust to continue evolving alongside the Rust ecosystem and hope to continue to participate in discussions around how Rust can be integrated into existing build systems.
Thank you to Matthew Maurer, Jeff Vander Stoep, Joel Galenson, Manish Goregaokar, and Tyler Mandry for their contributions to this post.
This can be mitigated to some extent with workspaces, but requires a very specific directory arrangement that AOSP does not conform to. ↩
This presents no problem for C/C++ and similar languages as the path to the generated source is provided directly to the compiler. ↩
Since include! works by textual inclusion, it may reference values from the enclosing namespace, modify the namespace, or use constructs like #![foo]. These implicit interactions can be difficult to maintain. Macros should be preferred if interaction with the rest of the crate is truly required. ↩
While libstd would usually be shareable for the same compiler revision, most other libraries would end up with several copies for Cargo-built Rust binaries, since each build would attempt to use a minimum feature set and may select different dependency versions for the library in question. Since information propagates across crate boundaries, you cannot simply produce a “most general” instance of that library. ↩
In our previous post, we announced that Android now supports the Rust programming language for developing the OS itself. Related to this, we are also participating in the effort to evaluate the use of Rust as a supported language for developing the Linux kernel. In this post, we discuss some technical aspects of this work using a few simple examples.
C has been the language of choice for writing kernels for almost half a century because it offers the level of control and predictable performance required by such a critical component. Density of memory safety bugs in the Linux kernel is generally quite low due to high code quality, high standards of code review, and carefully implemented safeguards. However, memory safety bugs do still regularly occur. On Android, vulnerabilities in the kernel are generally considered high-severity because they can result in a security model bypass due to the privileged mode that the kernel runs in.
We feel that Rust is now ready to join C as a practical language for implementing the kernel. It can help us reduce the number of potential bugs and security vulnerabilities in privileged code while playing nicely with the core kernel and preserving its performance characteristics.
We developed an initial prototype of the Binder driver to allow us to make meaningful comparisons between the safety and performance characteristics of the existing C version and its Rust counterpart. The Linux kernel has over 30 million lines of code, so naturally our goal is not to convert it all to Rust but rather to allow new code to be written in Rust. We believe this incremental approach allows us to benefit from the kernel’s existing high-performance implementation while providing kernel developers with new tools to improve memory safety and maintain performance going forward.
We joined the Rust for Linux organization, where the community had already done and continues to do great work toward adding Rust support to the Linux kernel build system. We also need designs that allow code in the two languages to interact with each other: we're particularly interested in safe, zero-cost abstractions that allow Rust code to use kernel functionality written in C, and how to implement functionality in idiomatic Rust that can be called seamlessly from the C portions of the kernel.
Since Rust is a new language for the kernel, we also have the opportunity to enforce best practices in terms of documentation and uniformity. For example, we have specific machine-checked requirements around the usage of unsafe code: for every unsafe function, the developer must document the requirements that need to be satisfied by callers to ensure that its usage is safe; additionally, for every call to unsafe functions (or usage of unsafe constructs like dereferencing a raw pointer), the developer must document the justification for why it is safe to do so.
Just as important as safety, Rust support needs to be convenient and helpful for developers to use. Let’s get into a few examples of how Rust can assist kernel developers in writing drivers that are safe and correct.
We'll use an implementation of a semaphore character device. Each device has a current value; writes of n bytes result in the device value being incremented by n; reads decrement the value by 1 unless the value is 0, in which case they will block until they can decrement the count without going below 0.
Suppose semaphore is a file representing our device. We can interact with it from the shell as follows:
> cat semaphore
When semaphore is a newly initialized device, the command above will block because the device's current value is 0. It will be unblocked if we run the following command from another shell because it increments the value by 1, which allows the original read to complete:
> echo -n a > semaphore
We could also increment the count by more than 1 if we write more data, for example:
> echo -n abc > semaphore
increments the count by 3, so the next 3 reads won't block.
To allow us to show a few more aspects of Rust, we'll add the following features to our driver: remember what the maximum value was throughout the lifetime of a device, and remember how many reads each file issued on the device.
We'll now show how such a driver would be implemented in Rust, contrasting it with a C implementation. We note, however, we are still early on so this is all subject to change in the future. How Rust can assist the developer is the aspect that we'd like to emphasize. For example, at compile time it allows us to eliminate or greatly reduce the chances of introducing classes of bugs, while at the same time remaining flexible and having minimal overhead.
A developer needs to do the following to implement a driver for a new character device in Rust:
The following outlines how the first two steps of our example compare in Rust and C:
impl FileOpener<Arc<Semaphore>> for FileState { fn open( shared: &Arc<Semaphore> ) -> KernelResult<Box<Self>> { [...] } } impl FileOperations for FileState { type Wrapper = Box<Self>; fn read( &self, _: &File, data: &mut UserSlicePtrWriter, offset: u64 ) -> KernelResult<usize> { [...] } fn write( &self, data: &mut UserSlicePtrReader, _offset: u64 ) -> KernelResult<usize> { [...] } fn ioctl( &self, file: &File, cmd: &mut IoctlCommand ) -> KernelResult<i32> { [...] } fn release(_obj: Box<Self>, _file: &File) { [...] } declare_file_operations!(read, write, ioctl); }
static int semaphore_open(struct inode *nodp, struct file *filp) { struct semaphore_state *shared = container_of(filp->private_data, struct semaphore_state, miscdev); [...] } static ssize_t semaphore_write(struct file *filp, const char __user *buffer, size_t count, loff_t *ppos) { struct file_state *state = filp->private_data; [...] } static ssize_t semaphore_read(struct file *filp, char __user *buffer, size_t count, loff_t *ppos) { struct file_state *state = filp->private_data; [...] } static long semaphore_ioctl(struct file *filp, unsigned int cmd, unsigned long arg) { struct file_state *state = filp->private_data; [...] } static int semaphore_release(struct inode *nodp, struct file *filp) { struct file_state *state = filp->private_data; [...] } static const struct file_operations semaphore_fops = { .owner = THIS_MODULE, .open = semaphore_open, .read = semaphore_read, .write = semaphore_write, .compat_ioctl = semaphore_ioctl, .release = semaphore_release, };
Character devices in Rust benefit from a number of safety features:
For a driver to provide a custom ioctl handler, it needs to implement the ioctl function that is part of the FileOperations trait, as exemplified in the table below.
fn ioctl( &self, file: &File, cmd: &mut IoctlCommand ) -> KernelResult<i32> { cmd.dispatch(self, file) } impl IoctlHandler for FileState { fn read( &self, _file: &File, cmd: u32, writer: &mut UserSlicePtrWriter ) -> KernelResult<i32> { match cmd { IOCTL_GET_READ_COUNT => { writer.write( &self .read_count .load(Ordering::Relaxed))?; Ok(0) } _ => Err(Error::EINVAL), } } fn write( &self, _file: &File, cmd: u32, reader: &mut UserSlicePtrReader ) -> KernelResult<i32> { match cmd { IOCTL_SET_READ_COUNT => { self .read_count .store(reader.read()?, Ordering::Relaxed); Ok(0) } _ => Err(Error::EINVAL), } } }
#define IOCTL_GET_READ_COUNT _IOR('c', 1, u64) #define IOCTL_SET_READ_COUNT _IOW('c', 1, u64) static long semaphore_ioctl(struct file *filp, unsigned int cmd, unsigned long arg) { struct file_state *state = filp->private_data; void __user *buffer = (void __user *)arg; u64 value; switch (cmd) { case IOCTL_GET_READ_COUNT: value = atomic64_read(&state->read_count); if (copy_to_user(buffer, &value, sizeof(value))) return -EFAULT; return 0; case IOCTL_SET_READ_COUNT: if (copy_from_user(&value, buffer, sizeof(value))) return -EFAULT; atomic64_set(&state->read_count, value); return 0; default: return -EINVAL; } }
Ioctl commands are standardized such that, given a command, we know whether a user buffer is provided, its intended use (read, write, both, none), and its size. In Rust, we provide a dispatcher (accessible by calling cmd.dispatch) that uses this information to automatically create user memory access helpers and pass them to the caller.
A driver is not required to use this though. If, for example, it doesn't use the standard ioctl encoding, Rust offers the flexibility of simply calling cmd.raw to extract the raw arguments and using them to handle the ioctl (potentially with unsafe code, which will need to be justified).
However, if a driver implementation does use the standard dispatcher, it will benefit from not having to implement any unsafe code, and:
All of the above could potentially also be done in C, but it's very easy for developers to (likely unintentionally) break contracts that lead to unsafety; Rust requires unsafe blocks for this, which should only be used in rare cases and brings additional scrutiny. Additionally, Rust offers the following:
We allow developers to use mutexes and spinlocks to provide interior mutability. In our example, we use a mutex to protect mutable data; in the tables below we show the data structures we use in C and Rust, and how we implement a wait until the count is nonzero so that we can satisfy a read:
struct SemaphoreInner { count: usize, max_seen: usize, } struct Semaphore { changed: CondVar, inner: Mutex<SemaphoreInner>, } struct FileState { read_count: AtomicU64, shared: Arc<Semaphore>, }
struct semaphore_state { struct kref ref; struct miscdevice miscdev; wait_queue_head_t changed; struct mutex mutex; size_t count; size_t max_seen; }; struct file_state { atomic64_t read_count; struct semaphore_state *shared; };
fn consume(&self) -> KernelResult { let mut inner = self.shared.inner.lock(); while inner.count == 0 { if self.shared.changed.wait(&mut inner) { return Err(Error::EINTR); } } inner.count -= 1; Ok(()) }
static int semaphore_consume( struct semaphore_state *state) { DEFINE_WAIT(wait); mutex_lock(&state->mutex); while (state->count == 0) { prepare_to_wait(&state->changed, &wait, TASK_INTERRUPTIBLE); mutex_unlock(&state->mutex); schedule(); finish_wait(&state->changed, &wait); if (signal_pending(current)) return -EINTR; mutex_lock(&state->mutex); } state->count--; mutex_unlock(&state->mutex); return 0; }
We note that such waits are not uncommon in the existing C code, for example, a pipe waiting for a "partner" to write, a unix-domain socket waiting for data, an inode search waiting for completion of a delete, or a user-mode helper waiting for state change.
The following are benefits from the Rust implementation:
In the tables below, we show how open, read, and write are implemented in our example driver:
fn read( &self, _: &File, data: &mut UserSlicePtrWriter, offset: u64 ) -> KernelResult<usize> { if data.is_empty() || offset > 0 { return Ok(0); } self.consume()?; data.write_slice(&[0u8; 1])?; self.read_count.fetch_add(1, Ordering::Relaxed); Ok(1) }
static ssize_t semaphore_read(struct file *filp, char __user *buffer, size_t count, loff_t *ppos) { struct file_state *state = filp->private_data; char c = 0; int ret; if (count == 0 || *ppos > 0) return 0; ret = semaphore_consume(state->shared); if (ret) return ret; if (copy_to_user(buffer, &c, sizeof(c))) return -EFAULT; atomic64_add(1, &state->read_count); *ppos += 1; return 1; }
fn write( &self, data: &mut UserSlicePtrReader, _offset: u64 ) -> KernelResult<usize> { { let mut inner = self.shared.inner.lock(); inner.count = inner.count.saturating_add(data.len()); if inner.count > inner.max_seen { inner.max_seen = inner.count; } } self.shared.changed.notify_all(); Ok(data.len()) }
static ssize_t semaphore_write(struct file *filp, const char __user *buffer, size_t count, loff_t *ppos) { struct file_state *state = filp->private_data; struct semaphore_state *shared = state->shared; mutex_lock(&shared->mutex); shared->count += count; if (shared->count < count) shared->count = SIZE_MAX; if (shared->count > shared->max_seen) shared->max_seen = shared->count; mutex_unlock(&shared->mutex); wake_up_all(&shared->changed); return count; }
fn open( shared: &Arc<Semaphore> ) -> KernelResult<Box<Self>> { Ok(Box::try_new(Self { read_count: AtomicU64::new(0), shared: shared.clone(), })?) }
static int semaphore_open(struct inode *nodp, struct file *filp) { struct semaphore_state *shared = container_of(filp->private_data, struct semaphore_state, miscdev); struct file_state *state; state = kzalloc(sizeof(*state), GFP_KERNEL); if (!state) return -ENOMEM; kref_get(&shared->ref); state->shared = shared; atomic64_set(&state->read_count, 0); filp->private_data = state; return 0; }
They illustrate other benefits brought by Rust:
The examples above are only a small part of the whole project. We hope it gives readers a glimpse of the kinds of benefits that Rust brings. At the moment we have nearly all generic kernel functionality needed by Binder neatly wrapped in safe Rust abstractions, so we are in the process of gathering feedback from the broader Linux kernel community with the intent of upstreaming the existing Rust support.
We also continue to make progress on our Binder prototype, implement additional abstractions, and smooth out some rough edges. This is an exciting time and a rare opportunity to potentially influence how the Linux kernel is developed, as well as inform the evolution of the Rust language. We invite those interested to join us in Rust for Linux and attend our planned talk at Linux Plumbers Conference 2021!
Thanks Nick Desaulniers, Kees Cook, and Adrian Taylor for contributions to this post. Special thanks to Jeff Vander Stoep for contributions and editing, and to Greg Kroah-Hartman for reviewing and contributing to the code examples.