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Make architecture more informative

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Call out boundaries and invariants
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Aleksey Kladov 2021-02-02 21:59:27 +03:00
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@ -9,8 +9,9 @@ $ cargo test
should be enough to get you started!
To learn more about how rust-analyzer works, see
[./architecture.md](./architecture.md) document.
To learn more about how rust-analyzer works, see [./architecture.md](./architecture.md) document.
It also explains the high-level layout of the source code.
Do skim through that document.
We also publish rustdoc docs to pages:
@ -99,25 +100,6 @@ I don't have a specific workflow for this case.
Additionally, I use `cargo run --release -p rust-analyzer -- analysis-stats path/to/some/rust/crate` to run a batch analysis.
This is primarily useful for performance optimizations, or for bug minimization.
## Parser Tests
Tests for the parser (`parser`) live in the `syntax` crate (see `test_data` directory).
There are two kinds of tests:
* Manually written test cases in `parser/ok` and `parser/err`
* "Inline" tests in `parser/inline` (these are generated) from comments in `parser` crate.
The purpose of inline tests is not to achieve full coverage by test cases, but to explain to the reader of the code what each particular `if` and `match` is responsible for.
If you are tempted to add a large inline test, it might be a good idea to leave only the simplest example in place, and move the test to a manual `parser/ok` test.
To update test data, run with `UPDATE_EXPECT` variable:
```bash
env UPDATE_EXPECT=1 cargo qt
```
After adding a new inline test you need to run `cargo xtest codegen` and also update the test data as described above.
## TypeScript Tests
If you change files under `editors/code` and would like to run the tests and linter, install npm and run:
@ -128,73 +110,6 @@ npm ci
npm run lint
```
# Code organization
All Rust code lives in the `crates` top-level directory, and is organized as a single Cargo workspace.
The `editors` top-level directory contains code for integrating with editors.
Currently, it contains the plugin for VS Code (in TypeScript).
The `docs` top-level directory contains both developer and user documentation.
We have some automation infra in Rust in the `xtask` package.
It contains stuff like formatting checking, code generation and powers `cargo xtask install`.
The latter syntax is achieved with the help of cargo aliases (see `.cargo` directory).
# Architecture Invariants
This section tries to document high-level design constraints, which are not
always obvious from the low-level code.
## Incomplete syntax trees
Syntax trees are by design incomplete and do not enforce well-formedness.
If an AST method returns an `Option`, it *can* be `None` at runtime, even if this is forbidden by the grammar.
## LSP independence
rust-analyzer is independent from LSP.
It provides features for a hypothetical perfect Rust-specific IDE client.
Internal representations are lowered to LSP in the `rust-analyzer` crate (the only crate which is allowed to use LSP types).
## IDE/Compiler split
There's a semi-hard split between "compiler" and "IDE", at the `hir` crate.
Compiler derives new facts about source code.
It explicitly acknowledges that not all info is available (i.e. you can't look at types during name resolution).
IDE assumes that all information is available at all times.
IDE should use only types from `hir`, and should not depend on the underling compiler types.
`hir` is a facade.
## IDE API
The main IDE crate (`ide`) uses "Plain Old Data" for the API.
Rather than talking in definitions and references, it talks in Strings and textual offsets.
In general, API is centered around UI concerns -- the result of the call is what the user sees in the editor, and not what the compiler sees underneath.
The results are 100% Rust specific though.
Shout outs to LSP developers for popularizing the idea that "UI" is a good place to draw a boundary at.
## LSP is stateless
The protocol is implemented in the mostly stateless way.
A good mental model is HTTP, which doesn't store per-client state, and instead relies on devices like cookies to maintain an illusion of state.
If some action requires multi-step protocol, each step should be self-contained.
A good example here is code action resolving process.
TO display the lightbulb, we compute the list of code actions without computing edits.
Figuring out the edit is done in a separate `codeAction/resolve` call.
Rather than storing some `lazy_edit: Box<dyn FnOnce() -> Edit>` somewhere, we use a string ID of action to re-compute the list of actions during the resolve process.
(See [this post](https://rust-analyzer.github.io/blog/2020/09/28/how-to-make-a-light-bulb.html) for more details.)
The benefit here is that, generally speaking, the state of the world might change between `codeAction` and `codeAction` resolve requests, so any closure we store might become invalid.
While we don't currently implement any complicated refactors with complex GUI, I imagine we'd use the same techniques for refactors.
After clicking each "Next" button during refactor, the client would send all the info which server needs to re-recreate the context from scratch.
## CI
CI does not test rust-analyzer, CI is a core part of rust-analyzer, and is maintained with above average standard of quality.
CI is reproducible -- it can only be broken by changes to files in this repository, any dependence on externalities is a bug.
# Code Style & Review Process
Do see [./style.md](./style.md).

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# Architecture
This document describes the high-level architecture of rust-analyzer.
If you want to familiarize yourself with the code base, you are just
in the right place!
If you want to familiarize yourself with the code base, you are just in the right place!
See also the [guide](./guide.md), which walks through a particular snapshot of
rust-analyzer code base.
See also the [guide](./guide.md), which walks through a particular snapshot of rust-analyzer code base.
Yet another resource is this playlist with videos about various parts of the
analyzer:
Yet another resource is this playlist with videos about various parts of the analyzer:
https://www.youtube.com/playlist?list=PL85XCvVPmGQho7MZkdW-wtPtuJcFpzycE
Note that the guide and videos are pretty dated, this document should be in
generally fresher.
Note that the guide and videos are pretty dated, this document should be in generally fresher.
## The Big Picture
See also this implementation-oriented blog posts:
* https://rust-analyzer.github.io/blog/2019/11/13/find-usages.html
* https://rust-analyzer.github.io/blog/2020/07/20/three-architectures-for-responsive-ide.html
* https://rust-analyzer.github.io/blog/2020/09/16/challeging-LR-parsing.html
* https://rust-analyzer.github.io/blog/2020/09/28/how-to-make-a-light-bulb.html
* https://rust-analyzer.github.io/blog/2020/10/24/introducing-ungrammar.html
## Bird's Eye View
![](https://user-images.githubusercontent.com/1711539/50114578-e8a34280-0255-11e9-902c-7cfc70747966.png)
On the highest level, rust-analyzer is a thing which accepts input source code
from the client and produces a structured semantic model of the code.
On the highest level, rust-analyzer is a thing which accepts input source code from the client and produces a structured semantic model of the code.
More specifically, input data consists of a set of test files (`(PathBuf,
String)` pairs) and information about project structure, captured in the so
called `CrateGraph`. The crate graph specifies which files are crate roots,
which cfg flags are specified for each crate and what dependencies exist between
the crates. The analyzer keeps all this input data in memory and never does any
IO. Because the input data are source code, which typically measures in tens of
megabytes at most, keeping everything in memory is OK.
More specifically, input data consists of a set of test files (`(PathBuf, String)` pairs) and information about project structure, captured in the so called `CrateGraph`.
The crate graph specifies which files are crate roots, which cfg flags are specified for each crate and what dependencies exist between the crates.
This the input (ground) state.
The analyzer keeps all this input data in memory and never does any IO.
Because the input data are source code, which typically measures in tens of megabytes at most, keeping everything in memory is OK.
A "structured semantic model" is basically an object-oriented representation of
modules, functions and types which appear in the source code. This representation
is fully "resolved": all expressions have types, all references are bound to
declarations, etc.
A "structured semantic model" is basically an object-oriented representation of modules, functions and types which appear in the source code.
This representation is fully "resolved": all expressions have types, all references are bound to declarations, etc.
This is derived state.
The client can submit a small delta of input data (typically, a change to a
single file) and get a fresh code model which accounts for changes.
The client can submit a small delta of input data (typically, a change to a single file) and get a fresh code model which accounts for changes.
The underlying engine makes sure that model is computed lazily (on-demand) and
can be quickly updated for small modifications.
The underlying engine makes sure that model is computed lazily (on-demand) and can be quickly updated for small modifications.
## Code generation
## Code Map
Some of the components of this repository are generated through automatic
processes. `cargo xtask codegen` runs all generation tasks. Generated code is
committed to the git repository.
This section talks briefly about various important directories an data structures.
Pay attention to the **Architecture Invariant** sections.
They often talk about things which are deliberately absent in the source code.
In particular, `cargo xtask codegen` generates:
Note also which crates are **API Boundaries**.
Remember, [rules at the boundary are different](https://www.tedinski.com/2018/02/06/system-boundaries.html).
1. [`syntax_kind/generated`](https://github.com/rust-analyzer/rust-analyzer/blob/a0be39296d2925972cacd9fbf8b5fb258fad6947/crates/ra_parser/src/syntax_kind/generated.rs)
-- the set of terminals and non-terminals of rust grammar.
### `xtask`
2. [`ast/generated`](https://github.com/rust-analyzer/rust-analyzer/blob/a0be39296d2925972cacd9fbf8b5fb258fad6947/crates/ra_syntax/src/ast/generated.rs)
-- AST data structure.
This is rust-analyzer's "build system".
We use cargo to compile rust code, but there are also various other tasks, like release management or local installation.
They are handled by Rust code in the xtask directory.
3. [`doc_tests/generated`](https://github.com/rust-analyzer/rust-analyzer/blob/a0be39296d2925972cacd9fbf8b5fb258fad6947/crates/assists/src/doc_tests/generated.rs),
[`test_data/parser/inline`](https://github.com/rust-analyzer/rust-analyzer/tree/a0be39296d2925972cacd9fbf8b5fb258fad6947/crates/ra_syntax/test_data/parser/inline)
-- tests for assists and the parser.
### `editors/code`
The source for 1 and 2 is in [`ast_src.rs`](https://github.com/rust-analyzer/rust-analyzer/blob/a0be39296d2925972cacd9fbf8b5fb258fad6947/xtask/src/ast_src.rs).
VS Code plugin.
## Code Walk-Through
### `libs/`
### `crates/ra_syntax`, `crates/parser`
rust-analyzer independent libraries which we publish to crates.io.
It not heavily utilized at the moment.
Rust syntax tree structure and parser. See
[RFC](https://github.com/rust-lang/rfcs/pull/2256) and [./syntax.md](./syntax.md) for some design notes.
### `crates/parser`
It is a hand-written recursive descent parser, which produces a sequence of events like "start node X", "finish node Y".
It works similarly to
[kotlin's parser](https://github.com/JetBrains/kotlin/blob/4d951de616b20feca92f3e9cc9679b2de9e65195/compiler/frontend/src/org/jetbrains/kotlin/parsing/KotlinParsing.java),
which is a good source of inspiration for dealing with syntax errors and incomplete input.
Original [libsyntax parser](https://github.com/rust-lang/rust/blob/6b99adeb11313197f409b4f7c4083c2ceca8a4fe/src/libsyntax/parse/parser.rs) is what we use for the definition of the Rust language.
`TreeSink` and `TokenSource` traits bridge the tree-agnostic parser from `grammar` with `rowan` trees.
**Architecture Invariant:** the parser is independent of the particular tree structure and particular representation of the tokens.
It transforms one flat stream of events into another flat stream of events.
Token independence allows us to pares out both text-based source code and `tt`-based macro input.
Tree independence allows us to more easily vary the syntax tree implementation.
It should also unlock efficient light-parsing approaches.
For example, you can extract the set of names defined in a file (for typo correction) without building a syntax tree.
**Architecture Invariant:** parsing never fails, the parser produces `(T, Vec<Error>)` rather than `Result<T, Error>`.
### `crates/syntax`
Rust syntax tree structure and parser.
See [RFC](https://github.com/rust-lang/rfcs/pull/2256) and [./syntax.md](./syntax.md) for some design notes.
- [rowan](https://github.com/rust-analyzer/rowan) library is used for constructing syntax trees.
- `grammar` module is the actual parser. It is a hand-written recursive descent parser, which
produces a sequence of events like "start node X", "finish node Y". It works similarly to [kotlin's parser](https://github.com/JetBrains/kotlin/blob/4d951de616b20feca92f3e9cc9679b2de9e65195/compiler/frontend/src/org/jetbrains/kotlin/parsing/KotlinParsing.java),
which is a good source of inspiration for dealing with syntax errors and incomplete input. Original [libsyntax parser](https://github.com/rust-lang/rust/blob/6b99adeb11313197f409b4f7c4083c2ceca8a4fe/src/libsyntax/parse/parser.rs)
is what we use for the definition of the Rust language.
- `TreeSink` and `TokenSource` traits bridge the tree-agnostic parser from `grammar` with `rowan` trees.
- `ast` provides a type safe API on top of the raw `rowan` tree.
- `ast_src` description of the grammar, which is used to generate `syntax_kinds`
and `ast` modules, using `cargo xtask codegen` command.
- `ungrammar` description of the grammar, which is used to generate `syntax_kinds` and `ast` modules, using `cargo xtask codegen` command.
Tests for ra_syntax are mostly data-driven: `test_data/parser` contains subdirectories with a bunch of `.rs`
(test vectors) and `.txt` files with corresponding syntax trees. During testing, we check
`.rs` against `.txt`. If the `.txt` file is missing, it is created (this is how you update
tests). Additionally, running `cargo xtask codegen` will walk the grammar module and collect
all `// test test_name` comments into files inside `test_data/parser/inline` directory.
Tests for ra_syntax are mostly data-driven.
`test_data/parser` contains subdirectories with a bunch of `.rs` (test vectors) and `.txt` files with corresponding syntax trees.
During testing, we check `.rs` against `.txt`.
If the `.txt` file is missing, it is created (this is how you update tests).
Additionally, running `cargo xtask codegen` will walk the grammar module and collect all `// test test_name` comments into files inside `test_data/parser/inline` directory.
Note
[`api_walkthrough`](https://github.com/rust-analyzer/rust-analyzer/blob/2fb6af89eb794f775de60b82afe56b6f986c2a40/crates/ra_syntax/src/lib.rs#L190-L348)
To update test data, run with `UPDATE_EXPECT` variable:
```bash
env UPDATE_EXPECT=1 cargo qt
```
After adding a new inline test you need to run `cargo xtest codegen` and also update the test data as described above.
Note [`api_walkthrough`](https://github.com/rust-analyzer/rust-analyzer/blob/2fb6af89eb794f775de60b82afe56b6f986c2a40/crates/ra_syntax/src/lib.rs#L190-L348)
in particular: it shows off various methods of working with syntax tree.
See [#93](https://github.com/rust-analyzer/rust-analyzer/pull/93) for an example PR which
fixes a bug in the grammar.
See [#93](https://github.com/rust-analyzer/rust-analyzer/pull/93) for an example PR which fixes a bug in the grammar.
**Architecture Invariant:** `syntax` crate is completely independent from the rest of rust-analyzer, it knows nothing about salsa or LSP.
This is important because it is possible to useful tooling using only syntax tree.
Without semantic information, you don't need to be able to _build_ code, which makes the tooling more robust.
See also https://web.stanford.edu/~mlfbrown/paper.pdf.
You can view the `syntax` crate as an entry point to rust-analyzer.
`sytax` crate is an **API Boundary**.
**Architecture Invariant:** syntax tree is a value type.
The tree is fully determined by the contents of its syntax nodes, it doesn't need global context (like an interner) and doesn't store semantic info.
Using the tree as a store for semantic info is convenient in traditional compilers, but doesn't work nicely in the IDE.
Specifically, assists and refactors require transforming syntax trees, and that becomes awkward if you need to do something with the semantic info.
**Architecture Invariant:** syntax tree is build for a single file.
This is to enable parallel parsing of all files.
**Architecture Invariant:** Syntax trees are by design incomplete and do not enforce well-formedness.
If an AST method returns an `Option`, it *can* be `None` at runtime, even if this is forbidden by the grammar.
### `crates/base_db`
We use the [salsa](https://github.com/salsa-rs/salsa) crate for incremental and
on-demand computation. Roughly, you can think of salsa as a key-value store, but
it also can compute derived values using specified functions. The `base_db` crate
provides basic infrastructure for interacting with salsa. Crucially, it
defines most of the "input" queries: facts supplied by the client of the
analyzer. Reading the docs of the `base_db::input` module should be useful:
everything else is strictly derived from those inputs.
We use the [salsa](https://github.com/salsa-rs/salsa) crate for incremental and on-demand computation.
Roughly, you can think of salsa as a key-value store, but it also can compute derived values using specified functions. The `base_db` crate provides basic infrastructure for interacting with salsa.
Crucially, it defines most of the "input" queries: facts supplied by the client of the analyzer.
Reading the docs of the `base_db::input` module should be useful: everything else is strictly derived from those inputs.
### `crates/hir*` crates
**Architecture Invariant:** particularities of the build system are *not* the part of the ground state.
In particular, `base_db` knows nothing about cargo.
The `CrateGraph` structure is used to represent the dependencies between the crates abstractly.
HIR provides high-level "object oriented" access to Rust code.
**Architecture Invariant:** `base_db` doesn't know about file system and file paths.
Files are represented with opaque `FileId`, there's no operation to get an `std::path::Path` out of the `FileId`.
The principal difference between HIR and syntax trees is that HIR is bound to a
particular crate instance. That is, it has cfg flags and features applied. So,
the relation between syntax and HIR is many-to-one. The `source_binder` module
is responsible for guessing a HIR for a particular source position.
### `crates/hir_expand`, `crates/hir_def`, `crates/hir_ty`
Underneath, HIR works on top of salsa, using a `HirDatabase` trait.
These crates are the *brain* of rust-analyzer.
This is the compiler part of the IDE.
`hir_xxx` crates have a strong ECS flavor, in that they work with raw ids and
directly query the database.
`hir_xxx` crates have a strong ECS flavor, in that they work with raw ids and directly query the database.
There's little abstraction here.
These crates integrate deeply with salsa and chalk.
The top-level `hir` façade crate wraps ids into a more OO-flavored API.
Name resolution, macro expansion and type inference all happen here.
These crates also define various intermediate representations of the core.
`ItemTree` condenses a single `SyntaxTree` into a "summary" data structure, which is stable over modifications to function bodies.
`DefMap` contains the module tree of a crate and stores module scopes.
`Body` stores information about expressions.
**Architecture Invariant:** this crates are not, and will never be, an api boundary.
**Architecture Invariant:** these creates explicitly care about being incremental.
The core invariant we maintain is "typing inside a function's body never invalidates global derived data".
Ie, if you change body of `foo`, all facts about `bar` should remain intact.
**Architecture Invariant:** hir exists only in context of particular crate instance with specific CFG flags.
The same syntax may produce several instances of HIR if the crate participates in the crate graph more than once.
### `crates/hir`
The top-level `hir` crate is an **API Boundary**.
If you think about "using rust-analyzer as a library", `hir` crate is most likely the façade you'll be talking to.
It wraps ECS-style internal API into a more OO-flavored API (with an extra `db` argument for each call).
**Architecture Invariant:** `hir` provides a static, fully resolved view of the code.
While internal `hir_*` crates _compute_ things, `hir`, from the outside, looks like an inert data structure.
`hir` also handles the delicate task of going from syntax to the corresponding `hir`.
Remember that the mapping here is one-to-many.
See `Semantics` type and `source_to_def` module.
Note in particular a curious recursive structure in `source_to_def`.
We first resolve the parent _syntax_ node to the parent _hir_ element.
Then we ask the _hir_ parent what _syntax_ children does it have.
Then we look for our node in the set of children.
This is the heart of many IDE features, like goto definition, which start with figuring out a hir node at the cursor.
This is some kind of (yet unnamed) uber-IDE pattern, as it is present in Roslyn and Kotlin as well.
### `crates/ide`
A stateful library for analyzing many Rust files as they change. `AnalysisHost`
is a mutable entity (clojure's atom) which holds the current state, incorporates
changes and hands out `Analysis` --- an immutable and consistent snapshot of
the world state at a point in time, which actually powers analysis.
The `ide` crate build's on top of `hir` semantic model to provide high-level IDE features like completion or goto definition.
It is an **API Boundary**.
If you want to use IDE parts of rust-analyzer via LSP, custom flatbuffers-based protocol or just as a library in your text editor, this is the right API.
One interesting aspect of analysis is its support for cancellation. When a
change is applied to `AnalysisHost`, first all currently active snapshots are
canceled. Only after all snapshots are dropped the change actually affects the
database.
**Architecture Invariant:** `ide` crate's API is build out of POD types with public fields.
The API uses editor's terminology, it talks about offsets and string labels rathe than in terms of definitions or types.
It is effectively the view in MVC and viewmodel in [MVVM](https://en.wikipedia.org/wiki/Model%E2%80%93view%E2%80%93viewmodel).
All arguments and return types are conceptually serializable.
In particular, syntax tress and and hir types are generally absent from the API (but are used heavily in the implementation).
Shout outs to LSP developers for popularizing the idea that "UI" is a good place to draw a boundary at.
APIs in this crate are IDE centric: they take text offsets as input and produce
offsets and strings as output. This works on top of rich code model powered by
`hir`.
`ide` is also the first crate which has the notion of change over time.
`AnalysisHost` is a state to which you can transactonally `apply_change`.
`Analysis` is an immutable snapshot of the state.
Internally, `ide` is split across several crates. `ide_assists`, `ide_completion` and `ide_ssr` implement large isolated features.
`ide_db` implements common IDE functionality (notably, reference search is implemented here).
The `ide` contains a public API/façade, as well as implementation for a plethora of smaller features.
**Architecture Invariant:** `ide` crate strives to provide a _perfect_ API.
Although at the moment it has only one consumer, the LSP server, LSP *does not* influence it's API design.
Instead, we keep in mind a hypothetical _ideal_ client -- an IDE tailored specifically for rust, every nook and cranny of which is packed with Rust-specific goodies.
### `crates/rust-analyzer`
An LSP implementation which wraps `ide` into a language server protocol.
This crate defines the `rust-analyzer` binary, so it is the **entry point**.
It implements the language server.
### `crates/vfs`
**Architecture Invariant:** `rust-analyzer` is the only crate that knows about LSP and JSON serialization.
If you want to expose a datastructure `X` from ide to LSP, don't make it serializable.
Instead, create a serializable counterpart in `rust-analyzer` crate and manually convert between the two.
Although `hir` and `ide` don't do any IO, we need to be able to read
files from disk at the end of the day. This is what `vfs` does. It also
manages overlays: "dirty" files in the editor, whose "true" contents is
different from data on disk.
`GlobalState` is the state of the server.
The `main_loop` defines the server event loop which accepts requests and sends responses.
Requests that modify the state or might block user's typing are handled on the main thread.
All other requests are processed in background.
## Testing Infrastructure
**Architecture Invariant:** the server is stateless, a-la HTTP.
Sometimes state needs to be preserved between requests.
For example, "what is the `edit` for the fifth's completion item of the last completion edit?".
For this, the second request should include enough info to re-create the context from scratch.
This generally means including all the parameters of the original request.
Rust Analyzer has three interesting [systems
boundaries](https://www.tedinski.com/2018/04/10/making-tests-a-positive-influence-on-design.html)
to concentrate tests on.
`reload` module contains the code that handles configuration and Cargo.toml changes.
This is a tricky business.
The outermost boundary is the `rust-analyzer` crate, which defines an LSP
interface in terms of stdio. We do integration testing of this component, by
feeding it with a stream of LSP requests and checking responses. These tests are
known as "heavy", because they interact with Cargo and read real files from
disk. For this reason, we try to avoid writing too many tests on this boundary:
in a statically typed language, it's hard to make an error in the protocol
itself if messages are themselves typed.
**Architecture Invariant:** `rust-analyzer` should be partially available even when the build is broken.
Reloading process should not prevent IDE features from working.
The middle, and most important, boundary is `ide`. Unlike
`rust-analyzer`, which exposes API, `ide` uses Rust API and is intended to
use by various tools. Typical test creates an `AnalysisHost`, calls some
`Analysis` functions and compares the results against expectation.
### `crates/toolchain`, `crates/project_model`, `crates/flycheck`
The innermost and most elaborate boundary is `hir`. It has a much richer
vocabulary of types than `ide`, but the basic testing setup is the same: we
create a database, run some queries, assert result.
These crates deal with invoking `cargo` to learn about project structure and get compiler errors for the "check on save" feature.
They use `crates/path` heavily instead of `std::path`.
A single `rust-analyzer` process can serve many projects, so it is important that server's current directory does not leak.
### `crates/mbe`, `crated/tt`, `crates/proc_macro_api`, `crates/proc_macro_srv`
These crates implement macros as token tree -> token tree transforms.
They are independent from the rest of the code.
### `crates/vfs`, `crates/vfs-notify`
These crates implement a virtual fils system.
They provide consistent snapshots of the underlying file system and insulate messy OS paths.
**Architecture Invariant:** vfs doesn't assume a single unified file system.
IE, a single rust-analyzer process can act as a remote server for two different machines, where the same `/tmp/foo.rs` path points to different files.
For this reason, all path APIs generally take some existing path as a "file system witness".
### `crates/stdx`
This crate contains various non-rust-analyzer specific utils, which could have been in std.
### `crates/profile`
This crate contains utilities for CPU and memory profiling.
## Cross-Cutting Concerns
This sections talks about the things which are everywhere and nowhere in particular.
### Code generation
Some of the components of this repository are generated through automatic processes.
`cargo xtask codegen` runs all generation tasks.
Generated code is generally committed to the git repository.
There are tests to check that the generated code is fresh.
In particular, we generate:
* API for working with syntax trees (`syntax::ast`, the `ungrammar` crate).
* Various sections of the manual:
* features
* assists
* config
* Documentation tests for assists
**Architecture Invariant:** we avoid bootstrapping.
For codegen we need to parse Rust code.
Using rust-analyzer for that would work and would be fun, but it would also complicate the build process a lot.
For that reason, we use syn and manual string parsing.
### Cancellation
Let's say that the IDE is in the process of computing syntax highlighting, when the user types `foo`.
What should happen?
`rust-analyzer`s answer is that the highlighting process should be cancelled -- its results are now stale, and it also blocks modification of the inputs.
The salsa database maintains a global revision counter.
When applying a change, salsa bumps this counter and waits until all other threads using salsa finish.
If a thread does salsa-based computation and notices that the counter is incremented, it panics with a special value (see `Canceled::throw`).
That is, rust-analyzer requires unwinding.
`ide` is the boundary where the panic is caught and transformed into a `Result<T, Cancelled>`.
### Testing
Rust Analyzer has three interesting [systems boundaries](https://www.tedinski.com/2018/04/10/making-tests-a-positive-influence-on-design.html) to concentrate tests on.
The outermost boundary is the `rust-analyzer` crate, which defines an LSP interface in terms of stdio.
We do integration testing of this component, by feeding it with a stream of LSP requests and checking responses.
These tests are known as "heavy", because they interact with Cargo and read real files from disk.
For this reason, we try to avoid writing too many tests on this boundary: in a statically typed language, it's hard to make an error in the protocol itself if messages are themselves typed.
Heavy tests are only run when `RUN_SLOW_TESTS` env var is set.
The middle, and most important, boundary is `ide`.
Unlike `rust-analyzer`, which exposes API, `ide` uses Rust API and is intended to use by various tools.
Typical test creates an `AnalysisHost`, calls some `Analysis` functions and compares the results against expectation.
The innermost and most elaborate boundary is `hir`.
It has a much richer vocabulary of types than `ide`, but the basic testing setup is the same: we create a database, run some queries, assert result.
For comparisons, we use the `expect` crate for snapshot testing.
To test various analysis corner cases and avoid forgetting about old tests, we
use so-called marks. See the `marks` module in the `test_utils` crate for more.
To test various analysis corner cases and avoid forgetting about old tests, we use so-called marks.
See the `marks` module in the `test_utils` crate for more.
**Architecture Invariant:** rust-analyzer tests do not use libcore or libstd.
All required library code must be a part of the tests.
This ensures fast test execution.
**Architecture Invariant:** tests are data driven and do not test API.
Tests which directly call various API functions are a liability, because they make refactoring the API significantly more complicated.
So most of the tests look like this:
```rust
fn check(input: &str, expect: expect_test::Expect) {
// The single place that actually exercises a particular API
}
#[test]
fn foo() {
check("foo", expect![["bar"]]);
}
#[test]
fn spam() {
check("spam", expect![["eggs"]]);
}
// ...and a hundred more tests that don't care about the specific API at all.
```
To specify input data, we use a single string literal in a special format, which can describe a set of rust files.
See the `Fixture` type.
**Architecture Invariant:** all code invariants are tested by `#[test]` tests.
There's no additional checks in CI, formatting and tidy tests are run with `cargo test`.
**Architecture Invariant:** tests do not depend on any kind of external resources, they are perfectly reproducible.
### Observability
I've run out of steam here :)
rust-analyzer is a long-running process, so its important to understand what's going on inside.
We have hierarchical profiler (`RA_PROFILER=1`) and object counting (`RA_COUNT=1`).