Coding Guidelines

This document describes the coding guidelines for the Libra Core Rust codebase.

Code formatting

All code formatting is enforced with rustfmt with a project-specific configuration. Below is an example command to adhere to the Libra Core project conventions.

libra$ cargo fmt

Code analysis

Clippy is used to catch common mistakes and is run as a part of continuous integration. Before submitting your code for review, you can run clippy with our configuration:

libra$ ./scripts/clippy.sh

In general, we follow the recommendations from rust-lang-nursery. The remainder of this guide provides detailed guidelines on specific topics in order to achieve uniformity of the codebase.

Code documentation

Any public fields, functions, and methods should be documented with Rustdoc.

Please follow the conventions as detailed below for modules, structs, enums, and functions. The single line is used as a preview when navigating Rustdoc. As an example, see the 'Structs' and 'Enums' sections in the collections Rustdoc.

/// [Single line] One line summary description
///
/// [Longer description] Multiple lines, inline code
/// examples, invariants, purpose, usage, etc.
[Attributes] If attributes exist, add after Rustdoc

Example below:

/// Represents (x, y) of a 2-dimensional grid
///
/// A line is defined by 2 instances.
/// A plane is defined by 3 instances.
#[repr(C)]
struct Point {
    x: i32,
    y: i32,
}

Constants and fields

Describe the purpose and definition of this data.

Functions and methods

Document the following for each function:

The action the method performs - “This method adds a new transaction to the mempool.” Use active voice and present tense (i.e. adds/creates/checks/updates/deletes).
Describe how and why to use this method.
Any condition that must be met before calling the method.
State conditions under which the function will panic!() or returns an Error
Brief description of return values.
Any special behavior that is not obvious

README.md for top-level directories and other major components

Each major component of Libra Core needs to have a README.md file. Major components are:

top-level directories (e.g. libra/network, libra/language)
the most important crates in the system (e.g. vm_runtime)

This file should contain:

The conceptual documentation of the component.
A link to the external API documentation for the component.
A link to the master license of the project.
A link to the master contributing guide for the project.

A template for readmes:

# Component Name

[Summary line: Start with one sentence about this component.]

## Overview

* Describe the purpose of this component and how the code in  
this directory works.
* Describe the interaction of the code in this directory with  
the other components.
* Describe the security model and assumptions about the crates  
in this directory. Examples of how to describe the security  
assumptions will be added in the future.

## Implementation Details

* Describe how the component is modeled. For example, why is the
  code organized the way it is?
* Other relevant implementation details.

## API Documentation

For the external API of this crate refer to [Link to rustdoc API].

[For a top-level directory, link to the most important APIs within.]

## Contributing

Refer to the Libra Project contributing guide [LINK].

## License

Refer to the Libra Project License [LINK].

A good example of README.md is libra/network/README.md that describes the networking crate.

Code suggestions

In the following sections, we have suggested some best practices for a uniform codebase. We will investigate and identify the practices that can be enforced using Clippy. This information will evolve and improve over time.

Attributes

Make sure to use the appropriate attributes for handling dead code:

// For code that is intended for production usage in the future
#[allow(dead_code)]
// For code that is only intended for testing and
// has no intended production use
#[cfg(test)]

Avoid Deref polymorphism

Don't abuse the Deref trait to emulate inheritance between structs, and thus reuse methods. For more information, read here.

Comments

We recommend that you use // and /// comments rather than block comments /* ... */ for uniformity and simpler grepping.

Cloning

If x is reference counted, prefer Arc::clone(x) over x.clone(). Arc::clone(x) explicitly indicates that we are cloning x. This avoids confusion about whether we are performing an expensive clone of a struct, enum, other types, or just a cheap reference copy.

Also, if you are passing around Arc<T> types, consider using a newtype wrapper:

#[derive(Clone, Debug)]
pub struct Foo(Arc<FooInner>);

Concurrent types

Concurrent types such as CHashMap, AtomicUsize, etc. have an immutable borrow on self i.e. fn foo_mut(&self,...) in order to support concurrent access on interior mutating methods. Good practices (such as those in the examples mentioned) avoid exposing synchronization primitives externally (e.g. Mutex, RwLock) and document the method semantics and invariants clearly.

When to use channels vs concurrent types?

Listed below are high-level suggestions based on experience:

Channels are for ownership transfer, decoupling of types, and coarse-grained messages. They fit well for transferring ownership of data, distributing units of work, and communicating async results. Furthermore, they help break circular dependencies (e.g. struct Foo contains an Arc<Bar> and struct Bar contains an Arc<Foo> that leads to complex initialization).
Concurrent types (e.g. such as CHashMap or structs that have interior mutability building on Mutex, RwLock, etc.) are better suited for caches and states.

Error handling

Error handling suggestions follow the Rust book guidance. Rust groups errors into two major categories: recoverable and unrecoverable errors. Recoverable errors should be handled with Result. Our suggestions on unrecoverable errors are listed below:

Panic

panic!() - Runtime panic! should only be used when the resulting state cannot be processed going forward. It should not be used for any recoverable errors.
unwrap() - Unwrap should only be used for mutexes (e.g. lock().unwrap()) and test code. For all other use cases, prefer expect(). The only exception is if the error message is custom-generated, in which case use .unwrap_or_else(|| panic!("error: {}", foo))
expect() - Expect should be invoked when a system invariant is expected to be preserved. expect() is preferred over unwrap() and should contain a detailed error message on failure in most cases.
assert!() - This macro is kept in both debug/release and should be used to protect invariants of the system as necessary
unreachable!() - This macro will panic on code that should not be reached (violating an invariant) and can be used where appropriate.

Generics

Generics allow dynamic behavior (similar to trait methods) with static dispatch. As the number of generic type parameters increase, the difficulty of using the type/method also increases (e.g. consider the combination of trait bounds required for this type, duplicate trait bounds on related types, etc.). In order to avoid this complexity, we generally try to avoid using a large number of generic type parameters. We have found that converting code with a large number of generic objects to trait objects with dynamic dispatch often simplifies our code.

Getters/setters

Excluding test code, set field visibility to private as much as possible. Private fields allow constructors to enforce internal invariants. Implement getters for data that consumers may need, but avoid setters unless mutable state is necessary.

Public fields are most appropriate for struct types in the C spirit: compound, passive data structures without internal invariants. Naming suggestions follow the guidance here as shown below.

struct Foo {
    size: usize,
    key_to_value: HashMap<u32, u32>
}

impl Foo {
    /// Return a copy when inexpensive
    fn size(&self) -> usize {
        self.size
    }

    /// Borrow for expensive copies
    fn key_to_value(&self) -> &HashMap<u32, u32> {
        &self.key_to_value
    }

    /// Setter follows set_xxx pattern
    fn set_foo(&mut self, size: usize){
        self.size = size;
    }

    /// For a more complex getter, using get_XXX is acceptable
    /// (similar to HashMap) with well-defined and
    /// commented semantics
    fn get_value(&self, key: u32) -> Option<&u32> {
        self.key_to_value.get(&key)
    }
}

Logging

We currently use slog for logging.

error! - Error-level messages have the highest urgency in slog. An unexpected error has occurred (e.g. exceeded the maximum number of retries to complete an RPC or inability to store data to local storage).
warn! - Warn-level messages help notify admins about automatically handled issues (e.g. retrying a failed network connection or receiving the same message multiple times, etc.).
info! - Info-level messages are well suited for "one time" events (such as logging state on one-time startup and shutdown) or periodic events that are not frequently occurring - e.g. changing the validator set every day.
debug! - Debug-level messages can occur frequently (i.e. potentially > 1 message per second) and are not typically expected to be enabled in production.
trace! - Trace-level logging is typically only used for function entry/exit.

Testing

Unit tests

Ideally, all code should be unit tested. Unit test files should be in the same directory as mod.rs and their file names should end in _test.rs. A module to be tested should have the test modules annotated with #[cfg(test)]. For example, if in a crate there is a db module, the expected directory structure is as follows:

src/db                        -> directory of db module
src/db/mod.rs                 -> code of db module
src/db/read_test.rs           -> db test 1
src/db/write_test.rs          -> db test 2
src/db/access/mod.rs          -> directory of access submodule
src/db/access/access_test.rs  -> test of access submodule

Property-based tests

Libra contains property-based tests written in Rust using the proptest framework. Property-based tests generate random test cases and assert that invariants, also called properties, hold for the code under test.

Some examples of properties tested in Libra:

Every serializer and deserializer pair is tested for correctness with random inputs to the serializer. Any pair of functions that are inverses of each other can be tested this way.
The results of executing common transactions through the VM are tested using randomly generated scenarios and verified with an oracle.

A tutorial for proptest can be found in the proptest book.

References:

What is Property Based Testing? (includes a comparison with fuzzing)
An introduction to property-based testing
Choosing properties for property-based testing

Fuzzing

Libra contains harnesses for fuzzing crash-prone code like deserializers, using libFuzzer through cargo fuzz. For more examples, see the testsuite/libra_fuzzer directory.

Libra

Technical Papers

READMEs