hbbft/tests/net_dynamic_hb.rs

254 lines
9.1 KiB
Rust

extern crate failure;
extern crate hbbft;
#[macro_use]
extern crate proptest;
extern crate integer_sqrt;
extern crate rand;
extern crate threshold_crypto;
pub mod net;
use std::{collections, time};
use hbbft::dynamic_honey_badger::{Change, ChangeState, DynamicHoneyBadger, Input};
use hbbft::messaging::DistAlgorithm;
use net::proptest::{gen_seed, NetworkDimension, TestRng, TestRngSeed};
use net::NetBuilder;
use proptest::prelude::ProptestConfig;
use rand::{Rng, SeedableRng};
/// Choose a node's contribution for an epoch.
///
/// Selects randomly out of a slice, according to chosen batch and contribution sizes. The function
/// will not fail to do so, even if the queue is empty, returning a smaller or empty slice
/// `Vec` accordingly.
///
/// # Panics
///
/// The function asserts that `batch_size >= contribution_size`.
fn choose_contribution<R, T>(
rng: &mut R,
queue: &[T],
batch_size: usize,
contribution_size: usize,
) -> Vec<T>
where
R: rand::Rng,
T: Clone,
{
assert!(batch_size >= contribution_size);
let n = queue.len().min(batch_size);
let k = queue.len().min(contribution_size);
rand::seq::sample_slice(rng, &queue[0..n], k)
}
/// Test configuration for dynamic honey badger tests.
#[derive(Debug)]
struct TestConfig {
/// The desired network dimension.
dimension: NetworkDimension,
/// Total number of transactions to execute before finishing.
total_txs: usize,
/// Epoch batch size.
batch_size: usize,
/// Individual nodes contribution size.
contribution_size: usize,
/// Random number generator to be passed to subsystems.
seed: TestRngSeed,
}
prop_compose! {
/// Strategy to generate a test configuration.
fn arb_config()
(dimension in NetworkDimension::range(3, 15),
total_txs in 20..60usize,
batch_size in 10..20usize,
contribution_size in 1..10usize,
seed in gen_seed())
-> TestConfig {
TestConfig{
dimension, total_txs, batch_size, contribution_size, seed
}
}
}
/// Proptest wrapper for `do_drop_and_readd`.
proptest!{
#![proptest_config(ProptestConfig {
cases: 1, .. ProptestConfig::default()
})]
#[test]
#[cfg_attr(feature = "cargo-clippy", allow(unnecessary_operation))]
fn drop_and_readd(cfg in arb_config()) {
do_drop_and_readd(cfg)
}
}
/// Dynamic honey badger: Drop a validator node, demoting it to observer, then re-add it, all while
/// running a regular honey badger network.
#[cfg_attr(feature = "cargo-clippy", allow(needless_pass_by_value))]
fn do_drop_and_readd(cfg: TestConfig) {
let mut rng: TestRng = TestRng::from_seed(cfg.seed);
// First, we create a new test network with Honey Badger instances.
let mut net = NetBuilder::new(0..cfg.dimension.size())
.num_faulty(cfg.dimension.faulty())
// Limited to 15k messages per node.
.message_limit(15_000 * cfg.dimension.size() as usize)
// 30 secs per node.
.time_limit(time::Duration::from_secs(30 * cfg.dimension.size() as u64))
// Ensure runs are reproducible.
.rng(rng.gen::<TestRng>())
.using_step(move |node| {
println!("Constructing new dynamic honey badger node #{}", node.id);
DynamicHoneyBadger::builder()
.rng(node.rng)
.build(node.netinfo)
.expect("cannot build instance")
}).build()
.expect("could not construct test network");
// We will use the first correct node as the node we will remove from and re-add to the network.
// Note: This should be randomized using proptest.
let pivot_node_id: usize = *(net
.correct_nodes()
.nth(0)
.expect("expected at least one correct node")
.id());
println!("Will remove and readd node #{}", pivot_node_id);
// We generate a list of transaction we want to propose, for each node. All nodes will propose
// a number between 0..total_txs, chosen randomly.
let mut queues: collections::BTreeMap<_, Vec<usize>> = net
.nodes()
.map(|node| (*node.id(), (0..cfg.total_txs).collect()))
.collect();
// For each node, select transactions randomly from the queue and propose them.
for (id, queue) in &mut queues {
let proposal = choose_contribution(&mut rng, queue, cfg.batch_size, cfg.contribution_size);
println!("Node {:?} will propose: {:?}", id, proposal);
// The step will have its messages added to the queue automatically, we ignore the output.
let _ = net
.send_input(*id, Input::User(proposal))
.expect("could not send initial transaction");
}
// Afterwards, remove a specific node from the dynamic honey badger network.
net.broadcast_input(&Input::Change(Change::Remove(pivot_node_id)))
.expect("broadcasting failed");
// We are tracking (correct) nodes' state through the process by ticking them off individually.
let mut awaiting_removal: collections::BTreeSet<_> =
net.correct_nodes().map(|n| *n.id()).collect();
let mut awaiting_addition: collections::BTreeSet<_> =
net.correct_nodes().map(|n| *n.id()).collect();
let mut expected_outputs: collections::BTreeMap<_, collections::BTreeSet<_>> = net
.correct_nodes()
.map(|n| (*n.id(), (0..10).into_iter().collect()))
.collect();
// Run the network:
loop {
let (node_id, step) = net.crank_expect();
for change in step.output.iter().map(|output| output.change()) {
match change {
ChangeState::Complete(Change::Remove(pivot_node_id)) => {
println!("Node {:?} done removing.", node_id);
// Removal complete, tally:
awaiting_removal.remove(&node_id);
// Now we can add the node again. Public keys will be reused.
let pk = net[*pivot_node_id]
.algorithm()
.netinfo()
.secret_key()
.public_key();
let _ = net[node_id]
.algorithm_mut()
.handle_input(Input::Change(Change::Add(*pivot_node_id, pk)))
.expect("failed to send `Add` input");
}
ChangeState::Complete(Change::Add(pivot_node_id, _)) => {
println!("Node {:?} done adding.", node_id);
// Node added, ensure it has been removed first.
if awaiting_removal.contains(&node_id) {
panic!(
"Node {:?} reported a success `Add({}, _)` before `Remove({})`",
node_id, pivot_node_id, pivot_node_id
);
}
awaiting_addition.remove(&node_id);
}
_ => {
println!("Unhandled change: {:?}", change);
}
}
}
// Record whether or not we received some output.
let has_output = !step.output.is_empty();
// Find the node's input queue.
let queue: &mut Vec<_> = queues
.get_mut(&node_id)
.expect("queue for node disappeared");
// Examine potential algorithm output.
for batch in step.output {
println!(
"Received epoch {} batch on node {:?}.",
batch.epoch(),
node_id,
);
for tx in batch.iter() {
// Remove the confirmed contribution from the input queue.
let index = queue.iter().position(|v| v == tx);
if let Some(idx) = index {
assert_eq!(queue.remove(idx), *tx);
}
// Add it to the set of received outputs.
if !net[node_id].is_faulty() {
expected_outputs
.get_mut(&node_id)
.expect("output set disappeared")
.remove(tx);
}
}
}
// Check if we are done.
if expected_outputs.values().all(|s| s.is_empty())
&& awaiting_addition.is_empty()
&& awaiting_removal.is_empty()
{
// All outputs are empty and all nodes have removed and added the single pivot node.
break;
}
// If not done, check if we still want to propose something.
if has_output {
// Out of the remaining transactions, select a suitable amount.
let proposal =
choose_contribution(&mut rng, queue, cfg.batch_size, cfg.contribution_size);
let _ = net
.send_input(node_id, Input::User(proposal))
.expect("could not send follow-up transaction");
}
}
// As a final step, we verify that all nodes have arrived at the same conclusion.
let first = net.correct_nodes().nth(0).unwrap().outputs();
assert!(net.nodes().all(|node| node.outputs() == first));
println!("End result: {:?}", first);
}