pezkuwichain/pezkuwi-subxt
1
0
Fork 0
mirror of https://github.com/pezkuwichain/pezkuwi-subxt.git synced 2026-05-08 01:58:00 +00:00
Code Issues Packages Projects Releases Wiki Activity

[Documentation] Delete unused outdated polkadot/testing.md (#3559)

Browse Source 
# Description

*Deletes `testing.md` file in accordance with the discussion on issue
#2527.* Old references to Gurke or simnet have been removed.

Fixes #2527

---------

Co-authored-by: Bastian Köcher <git@kchr.de>
This commit is contained in:
philoniare
2024-03-05 18:46:56 +08:00
committed by GitHub
parent efcea0edab
commit 601b77d998
1 changed files with 0 additions and 302 deletions
Download Patch File Download Diff File Expand all files Collapse all files
polkadot/doc/testing.md
-302
View File
@@ -1,302 +0,0 @@
# Testing
Testing is an essential tool to assure correctness. This document describes how we test the Polkadot code, whether
locally, at scale, and/or automatically in CI.
## Scopes
The testing strategy for Polkadot is 4-fold:
### Unit testing (1)
Boring, small scale correctness tests of individual functions. It is usually
enough to run `cargo test` in the crate you are testing.
For full coverage you may have to pass some additional features. For example:
```sh
cargo test --features ci-only-tests
```
### Integration tests
There are the following variants of integration tests:
#### Subsystem tests (2)
One particular subsystem (subsystem under test) interacts with a mocked overseer that is made to assert incoming and
outgoing messages of the subsystem under test. See e.g. the `statement-distribution` tests.
#### Behavior tests (3)
Launching small scale networks, with multiple adversarial nodes. This should include tests around the thresholds in
order to evaluate the error handling once certain assumed invariants fail.
Currently, we commonly use **zombienet** to run mini test-networks, whether locally or in CI. To run on your machine:
- First, make sure you have [zombienet][zombienet] installed.
- Now, all the required binaries must be installed in your $PATH. You must run the following from the `polkadot/`
directory in order to test your changes. (Not `zombienet setup`, or you will get the released binaries without your
local changes!)
```sh
cargo install --path . --locked
```
- You will also need to install whatever binaries are required for your specific tests. For example, to install
`undying-collator`, from `polkadot/`, run:
```sh
cargo install --path ./parachain/test-parachains/undying/collator --locked
```
- Finally, run the zombienet test from the `polkadot` directory:
```sh
RUST_LOG=parachain::pvf=trace zombienet --provider=native spawn zombienet_tests/functional/0001-parachains-pvf.toml
```
- You can pick a validator node like `alice` from the output and view its logs
(`tail -f <log_file>`) or metrics. Make sure there is nothing funny in the logs
(try `grep WARN <log_file>`).
#### Testing at scale (4)
Launching many nodes with configurable network speed and node features in a cluster of nodes. At this scale the
[Simnet][simnet] comes into play which launches a full cluster of nodes. The scale is handled by spawning a kubernetes
cluster and the meta description is covered by [Gurke][Gurke]. Asserts are made using Grafana rules, based on the
existing prometheus metrics. This can be extended by adding an additional service translating `jaeger` spans into
addition prometheus avoiding additional Polkadot source changes.
_Behavior tests_ and _testing at scale_ have naturally soft boundary. The most significant difference is the presence of
a real network and the number of nodes, since a single host often not capable to run multiple nodes at once.
## Observing Logs
To verify expected behavior it's often useful to observe logs. To avoid too many
logs at once, you can run one test at a time:
1. Add `sp_tracing::try_init_simple();` to the beginning of a test
2. Specify `RUST_LOG=<target>::<subtarget>=trace` before the cargo command.
For example:
```sh
RUST_LOG=parachain::pvf=trace cargo test execute_can_run_serially
```
For more info on how our logs work, check [the docs][logs].
## Coverage
Coverage gives a _hint_ of the actually covered source lines by tests and test applications.
The state of the art is currently tarpaulin which unfortunately yields a lot of false negatives. Lines that
are in fact covered, marked as uncovered due to a mere linebreak in a statement can cause these artifacts. This leads to
lower coverage percentages than there actually is.
Since late 2020 rust has gained [MIR based coverage tooling](
https://blog.rust-lang.org/inside-rust/2020/11/12/source-based-code-coverage.html).
```sh
# setup
rustup component add llvm-tools-preview
cargo install grcov miniserve
export CARGO_INCREMENTAL=0
# wasm is not happy with the instrumentation
export SKIP_BUILD_WASM=true
export BUILD_DUMMY_WASM_BINARY=true
# the actully collected coverage data
export LLVM_PROFILE_FILE="llvmcoveragedata-%p-%m.profraw"
# build wasm without instrumentation
export WASM_TARGET_DIRECTORY=/tmp/wasm
cargo +nightly build
# required rust flags
export RUSTFLAGS="-Zinstrument-coverage"
# assure target dir is clean
rm -r target/{debug,tests}
# run tests to get coverage data
cargo +nightly test --all
# create the *html* report out of all the test binaries
# mostly useful for local inspection
grcov . --binary-path ./target/debug -s . -t html --branch --ignore-not-existing -o ./coverage/
miniserve -r ./coverage
# create a *codecov* compatible report
grcov . --binary-path ./target/debug/ -s . -t lcov --branch --ignore-not-existing --ignore "/*" -o lcov.info
```
The test coverage in `lcov` can the be published to <https://codecov.io>.
```sh
bash <(curl -s https://codecov.io/bash) -f lcov.info
```
or just printed as part of the PR using a github action i.e.
[`jest-lcov-reporter`](https://github.com/marketplace/actions/jest-lcov-reporter).
For full examples on how to use [`grcov` /w Polkadot specifics see the github
repo](https://github.com/mozilla/grcov#coverallscodecov-output).
## Fuzzing
Fuzzing is an approach to verify correctness against arbitrary or partially structured inputs.
Currently implemented fuzzing targets:
- `erasure-coding`
The tooling of choice here is `honggfuzz-rs` as it allows _fastest_ coverage according to "some paper" which is a
positive feature when run as part of PRs.
Fuzzing is generally not applicable for data secured by cryptographic hashes or signatures. Either the input has to be
specifically crafted, such that the discarded input percentage stays in an acceptable range. System level fuzzing is
hence simply not feasible due to the amount of state that is required.
Other candidates to implement fuzzing are:
- `rpc`
- ...
## Performance metrics
There are various ways of performance metrics.
- timing with `criterion`
- cache hits/misses w/ `iai` harness or `criterion-perf`
- `coz` a performance based compiler
Most of them are standard tools to aid in the creation of statistical tests regarding change in time of certain unit
tests.
`coz` is meant for runtime. In our case, the system is far too large to yield a sufficient number of measurements in
finite time. An alternative approach could be to record incoming package streams per subsystem and store dumps of them,
which in return could be replayed repeatedly at an accelerated speed, with which enough metrics could be obtained to
yield information on which areas would improve the metrics. This unfortunately will not yield much information, since
most if not all of the subsystem code is linear based on the input to generate one or multiple output messages, it is
unlikely to get any useful metrics without mocking a sufficiently large part of the other subsystem which overlaps with
[#Integration tests] which is unfortunately not repeatable as of now. As such the effort gain seems low and this is not
pursued at the current time.
## Writing small scope integration tests with preconfigured workers
Requirements:
- spawn nodes with preconfigured behaviors
- allow multiple types of configuration to be specified
- allow extendability via external crates
- ...
---
## Implementation of different behavior strain nodes
### Goals
The main goals are is to allow creating a test node which exhibits a certain behavior by utilizing a subset of _wrapped_
or _replaced_ subsystems easily. The runtime must not matter at all for these tests and should be simplistic. The
execution must be fast, this mostly means to assure a close to zero network latency as well as shorting the block time
and epoch times down to a few `100ms` and a few dozend blocks per epoch.
### Approach
#### MVP
A simple small scale builder pattern would suffice for stage one implementation of allowing to replace individual
subsystems. An alternative would be to harness the existing `AllSubsystems` type and replace the subsystems as needed.
#### Full `proc-macro` implementation
`Overseer` is a common pattern. It could be extracted as `proc` macro and generative `proc-macro`. This would replace
the `AllSubsystems` type as well as implicitly create the `AllMessages` enum as `AllSubsystemsGen` does today.
The implementation is yet to be completed, see the [implementation PR](https://github.com/paritytech/polkadot/pull/2962)
for details.
##### Declare an overseer implementation
```rust
struct BehaveMaleficient;
impl OverseerGen for BehaveMaleficient {
fn generate<'a, Spawner, RuntimeClient>(
&self,
args: OverseerGenArgs<'a, Spawner, RuntimeClient>,
) -> Result<(Overseer<Spawner, Arc<RuntimeClient>>, OverseerHandler), Error>
where
RuntimeClient: 'static + ProvideRuntimeApi<Block> + HeaderBackend<Block> + AuxStore,
RuntimeClient::Api: ParachainHost<Block> + BabeApi<Block> + AuthorityDiscoveryApi<Block>,
Spawner: 'static + overseer::gen::Spawner + Clone + Unpin,
{
let spawner = args.spawner.clone();
let leaves = args.leaves.clone();
let runtime_client = args.runtime_client.clone();
let registry = args.registry.clone();
let candidate_validation_config = args.candidate_validation_config.clone();
// modify the subsystem(s) as needed:
let all_subsystems = create_default_subsystems(args)?.
// or spawn an entirely new set
replace_candidate_validation(
// create the filtered subsystem
FilteredSubsystem::new(
CandidateValidationSubsystem::with_config(
candidate_validation_config,
Metrics::register(registry)?,
),
// an implementation of
Skippy::default(),
),
);
Overseer::new(leaves, all_subsystems, registry, runtime_client, spawner)
.map_err(|e| e.into())
// A builder pattern will simplify this further
// WIP https://github.com/paritytech/polkadot/pull/2962
}
}
fn main() -> eyre::Result<()> {
color_eyre::install()?;
let cli = Cli::from_args();
assert_matches::assert_matches!(cli.subcommand, None);
polkadot_cli::run_node(cli, BehaveMaleficient)?;
Ok(())
}
```
[`variant-a`](../node/malus/src/variant-a.rs) is a fully working example.
#### Simnet
Spawn a kubernetes cluster based on a meta description using [Gurke] with the [Simnet] scripts.
Coordinated attacks of multiple nodes or subsystems must be made possible via a side-channel, that is out of scope for
this document.
The individual node configurations are done as targets with a particular builder configuration.
#### Behavior tests w/o Simnet
Commonly this will require multiple nodes, and most machines are limited to running two or three nodes concurrently.
Hence, this is not the common case and is just an implementation _idea_.
```rust
behavior_testcase!{
"TestRuntime" =>
"Alice": <AvailabilityDistribution=DropAll, .. >,
"Bob": <AvailabilityDistribution=DuplicateSend, .. >,
"Charles": Default,
"David": "Charles",
"Eve": "Bob",
}
```
[zombienet]: https://github.com/paritytech/zombienet
[Gurke]: https://github.com/paritytech/gurke
[simnet]: https://github.com/paritytech/simnet_scripts
[logs]: https://github.com/paritytech/polkadot-sdk/blob/master/polkadot/node/gum/src/lib.rs