Thanks for considering helping this project. There are many ways you can help: using the library and reporting bugs, reporting usability issues, making additions and improvements to the library, documentation and finding security bugs.
Please file a github issue. Include as much information as possible. Suspected protocol bugs are easier debugged with a pcap or reproduction steps.
Feel free to file github issues to get help, or ask a question.
If you believe you've found a security bug please open a draft security advisory in GitHub, and not as a regular repository issue. See [SECURITY.md] for more information.
Some ideas and guidelines for contributions:
- For large features, file an issue prior to starting work. This means everyone can see what is in progress prior to a PR.
- Feel free to submit a PR even if the work is not totally finished, for feedback or to hand-over.
- Prefer not to reference github issue or PR numbers in commits.
- Try to keep code formatting commits separate from functional commits.
- See
.github/workflows/build.ymlfor how to run the various test suites, and how to make coverage measurements. - I run
cargo outdatedprior to major releases; but PRs to update specific dependencies are welcome.
We prefer to keep the commit history clean and easy to follow. As such, we prefer small commits that do one thing. In particular:
- Avoid mixing refactoring and functional changes in the same commit if possible
- Make mechanical changes (like renaming or moving code around) in a separate commit
- Isolate updates to
Cargo.lockin their own commits
Our default workflow is to rebase clean commit history from a PR to main.
Please report security bugs by opening a draft security advisory in GitHub, and not as a regular repository issue.
See [SECURITY.md] for more information.
If you're looking for security bugs, this crate is set up for
cargo fuzz but would benefit from more runtime, targets and corpora.
- Features involving additions to the public API should have (at least)
API-level tests (see
rustls/tests/api.rs). - Protocol additions should have some coverage -- consider enabling corresponding tests in the bogo suite, or writing some ad hoc tests.
PRs which cause test failures or a significant coverage decrease are unlikely to be accepted.
Within a module, we prefer to order items top-down. This means that items within a module will depend on items defined below them, but not (usually) above them. The idea here is that the public API, with more internal dependencies, will be read (and changed) more often, and putting it closer to the top of the module makes it more accessible.
This can be surprising to many engineers who are used to the bottom-up ordering used in languages like Python, where items can have a run-time dependency on other items defined in the same module.
Usually const values will thus go on the bottom of the module (least complex,
usually no dependencies of their own), although in larger modules it can make
sense to place a const directly below the user (especially if there is a
single user, or just a few co-located users).
The #[cfg(test)] mod tests {} module goes on the very bottom, if present.
For a given type, we prefer to order items as follows:
- The type definition (
structorenum) - The inherent
implblock (that is, not a trait implementation) implblocks for traits, from most specific to least specific. The least specific would be something like aDebugorCloneimpl.
Here's a guide to how we like to order associated functions:
- Associated functions (that is,
fn foo() {}instead offn foo(&self) {}) - Constructors, starting with the constructor that takes the least arguments
- Public API that takes a
&mut self - Public API that takes a
&self - Private API that takes a
&mut self - Private API that takes a
&self constvalues
Note that we usually also practice top-down ordering here; where these are in conflict, make a choice that you think makes sense. For getters and setters, the order should typically mirror the order of the fields in the type definition.
While single-use functions can make sense if the algorithm is sufficiently complex that it warrants an explicit name and interface, using many short single-use functions can make the code harder to follow, due to having to jump around in order to gain an understanding of what's going on. When writing a single-use function, consider whether it needs the dedicated interface, or if it could be inlined into its caller instead.
If a function's semantics or implementation are strongly dependent on one of its arguments, and the argument is defined in a type within the current crate, prefer using a method on the type. Similarly, if a function is taking multiple arguments that originate from the same common type in all call-sites it is a strong candidate for becoming a method on the type.
When writing a function, we prefer to order arguments from most specific to
least specific. This means that an image_id might go before the domain,
which will go before the app context. More specific arguments are more
differentiating between a given function and other functions, so putting them
first makes it easier to infer the context/meaning of the function (compared to
starting with a number of generic context-like types).
We prefer to use impl ... for arguments and return types when there's a single
use of the type. Generic type argument bounds add a level of indirection that's
harder to read in one pass.
Where possible, avoid writing validate or check type functions that try to
check for error conditions based on the state of a populated object. Prefer
"parse, don't validate"
style and try to use the type system to make it impossible for invalid states to
be represented.
We use Result types pervasively throughout the code to signal error cases.
Outside of unit/integration tests we prefer to avoid unwrap() and expect()
calls unless there is a clear invariant which can be locally validated by the
structure of the code. If there is such an invariant, we usually add a comment
explaining how the invariant is upheld. In other cases (especially for error
cases which can arise from network traffic, which could represent an attacker),
we always prefer to handle errors and ultimately return an error to the network
peer or close the connection.
We generally make full use of the expression-oriented nature of Rust. For
example, when using iterators we prefer to use map and other combinators
instead of for-loops when possible, and will often avoid variable bindings if
a variable is only used once. Naming variables takes cognitive efforts, and so
does tracking references to bindings in your mind. One metric we like to
minimize is the number of mutable bindings in a given scope.
Remember that the overall goal is to make the code easy to understand.
Combinators can help with this by eliding boilerplate (like replacing a
None => None arm with a map() call), but they can also make it harder to
understand the code. One example is that a combinator chain like
.map().map_err() might be harder to understand than a match statement
(since, in this case, both of the arms have a significant transformation).
The typed nature of Rust can cause some code to end up at deeply indented
levels, which we call "rightward drift". This makes lines shorter, making the
code harder to read. To avoid this, try to return early for error cases, or
continue early in a loop to skip an iteration.
When writing a match or if expression that has arms that each share a return
type (e.g. Ok(...)), hoist the commonality outside the match. This helps
separate out the important differences and reduces code duplication.
// Incorrect:
match foo {
1..10 => Ok(do_one_thing()),
_ => Ok(do_another()),
}
// Correct:
Ok(match foo {
1..10 => do_one_thing(),
_ => do_another(),
})When writing match expressions, try to avoid using ref in patterns. Prefer
taking a reference on the
scrutinee
of the match.
Since the addition of binding
modes for improved
match ergonomics the ref keyword is unidiomatic and can be unfamiliar to
readers.
We prefer concise names, especially for local variables, but prefer to
expand acronyms/abbreviations that are not very well known (e.g. prefer
key_usage instead of ku, anonymous instead of anon). Extremely common
short-forms like url are acceptable.
Avoid adding a suffix for a variable that describes its type (provided that its
type is hard to confuse with other types -- for example, we do still use _id
suffixes because we usually use numeric IDs for database entities). The
precision/conciseness trade-off for variable names also depends on the scope of
the binding.
Per the
API guidelines,
get_() prefixes are discouraged.
When implementing or modifying an enum type, list its variants in alphabetical
order. It's acceptable to ignore this advice when matching the order imposed by
an external source, e.g. a standards document.
Prefer active verbs for variant names. E.g. Allow instead of Allowed,
Forbid instead of Forbidden. Avoid faux-bools like Yes and No, instead
preferring variant names that are descriptive of the different states.
We prefer not to elide lifetimes when naming types that are generic over
lifetimes. Always include a lifetime placeholder (e.g. <'_>) to avoid
confusion.
We use 3 blocks of imports in our Rust files:
stdimports- Imports from external crates
- Crate-internal imports
We believe that this makes it easier to see where a particular import comes from.
Within the import blocks we prefer to separate imports that don't share a parent module. For example,
// Incorrect
use alloc::{format, vec::Vec};
// Correct
use alloc::format;
use alloc::vec::Vec;We prefer to reference types and traits by an imported symbol name instead of
using qualified references. Qualification paths generally add noise and are
unnecessary. The one exception to this is when the symbol name is overly
generic, or easily confused between different crates. In this case we prefer to
import the symbol name under an alias, or if the parent module name is short,
using a one-level qualified path. E.g. for a crate with a local Error type,
prefer to import std::error::Error as StdError.
We prefer to export types under a single name, avoiding re-exporting types from
the top-level lib.rs. The exception to this are "paved path" exports that we
expect every user will need. The canonical example of such types are
client::ClientConfig and server::ServerConfig. In general this sort of type
is rare and most new types should be exported only from the module in which they
are defined.
Prefer a numeric base that fits with the domain of the value being used. E.g.
use hexadecimal for protocol message literals, and octal for UNIX privileges.
Use digit grouping to make larger numeric constants easy to read, e.g. use
100_000_000 instead of 100000000.
We prefer to avoid type aliases as they obfuscate the underlying type and don't provide additional type safety. Using the newtype idiom is one alternative when an abstraction boundary is worth the added complexity.
Contributions are made under rustls's licenses.