Files
trueskill-tt/tests/cross_process_determinism.rs
T
logaritmiskandClaude Opus 5 dc1f4d5847 fix!: make the Time generic reachable
`History<T: Time, ..>` has always been generic over the time axis,
`Untimed` has always been exported, and `Drift<T>` is generic specifically
so that "seasonal or calendar-aware drift is expressible without going
through i64". None of it was reachable from a downstream crate.

Every construction route pinned `T = i64`: `History::builder()`,
`History::builder_with_key()`, and the only `Default` impl on
`HistoryBuilder`. Its fields are private and it had no `new`. So all three
escape routes failed to compile, and a consumer with domain timestamps
had to convert to i64 — which is the exact thing the parameter exists to
avoid. One of `History`'s four type parameters was paid for at every
signature and could never be varied.

`Default` is now generic over `T` and `K`, `HistoryBuilder::new()` exists,
and `time_type::<T2>()` / `key_type::<K2>()` join `drift` and `observer`
as type-changing setters:

    History::builder().time_type::<Untimed>().build()
    History::builder().key_type::<String>().build()
    HistoryBuilder::<Season, _, _, String>::new().build()

`key_type` replaces `builder_with_key`, which could not be turbofished —
`K` sat on the impl rather than the function, so callers had to spell
`History::<i64, _, _, String>::builder_with_key()`. 18 call sites across
15 files migrated.

tests/time_axis.rs is the part that matters. NOTHING in the repository
constructed a non-i64 history, which is precisely why this survived, so
the fix is only half done without a test that exercises the generic. It
defines a `Season(u16)` time type and a `SeasonalDrift` that accumulates
between seasons but not within one — the calendar-aware case the trait's
docs cite — and checks the whole path: fit, converge, and read a learning
curve whose times come back as `Season`, not as integers.

Two of the six tests are controls rather than assertions about output.
`Untimed` must ignore drift entirely, since elapsed is always zero, so
gamma 0.0 and gamma 5.0 must agree bit for bit. And a custom `Drift` must
actually widen a gap across seasons, or the test above would pass whether
or not the drift was consulted at all.

The README's ticked "Generalise a time axis" box is now true.

BREAKING CHANGE: `History::builder_with_key()` is removed. Use
`History::builder().key_type::<K>()`.

Closes #68

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
2026-09-09 20:19:16 +02:00

159 lines
5.1 KiB
Rust

//! Determinism across *processes*, which an in-process test cannot see.
//!
//! Rust seeds its default hasher once per process, so every `HashMap`
//! iteration order is fixed for a run and varies between runs. A test that
//! compares results within one process therefore cannot detect a float sum
//! whose order comes from a map — all its samples share one seed.
//!
//! That is not hypothetical. `tests/determinism.rs` compares four thread counts
//! inside one process and passed throughout, while `posterior_of` was returning
//! two distinct bit patterns across 40 separate runs on identical input.
//!
//! This re-executes the test binary and compares `f64::to_bits`.
use std::{env, process::Command};
use smallvec::smallvec;
use trueskill_tt::{
ConstantDrift, ConvergenceOptions, Event, History, Member, NullObserver, Outcome, Team,
UnknownKeys,
};
/// Set in the child so it reports instead of re-spawning.
const CHILD: &str = "TSTT_DETERMINISM_CHILD";
const RUNS: usize = 40;
type H = History<i64, ConstantDrift, NullObserver, String>;
fn fitted() -> H {
let mut h: H = History::builder()
.key_type::<String>()
.mu(0.0)
.sigma(6.0)
.beta(1.0)
.score_sigma(2.0)
.drift(ConstantDrift::new(0.05))
.unknown_keys(UnknownKeys::Prior)
.convergence(ConvergenceOptions {
max_iter: 20_000,
epsilon: 1e-13,
alpha: 1.0,
})
.build();
let mut events = Vec::new();
for t in 0..12i64 {
for k in 0..6usize {
let a = format!("p{}", (t as usize * 6 + k) % 10);
let b = format!("p{}", (t as usize * 6 + k + 4) % 10);
events.push(Event {
time: t,
teams: smallvec![
Team::with_members([Member::new(a)]),
Team::with_members([Member::new(b)]),
],
outcome: Outcome::scores([3.0, 1.0]),
});
}
}
h.add_events(events).unwrap();
assert!(h.converge().unwrap().converged);
h
}
/// Every quantity that could plausibly depend on iteration order, as bits.
fn fingerprint() -> String {
let h = fitted();
// Unknown keys with UNEQUAL but COMPARABLE coefficients, which is what
// makes the sum order-sensitive.
//
// Equal terms sum order-independently and would make this pass vacuously.
// Terms of wildly different magnitudes are no better: the small ones fall
// below the running total's ULP and are absorbed whatever the order —
// measured, spreading these over nine decades dropped the detection rate
// to roughly one run in forty. Comparable sizes keep every term able to
// change the last bits.
let ghosts: Vec<String> = (0..24).map(|i| format!("ghost{i}")).collect();
let mut terms: Vec<(&String, f64)> = ghosts
.iter()
.enumerate()
.map(|(i, k)| (k, 1.0 + i as f64 * 0.37))
.collect();
let known = "p0".to_string();
terms.push((&known, -1.0));
let posterior = h.posterior_of(&terms).unwrap();
let a = "p0".to_string();
let b = "p1".to_string();
let target = [(&a, 1.0), (&b, -1.0)];
let teams: [&[&String]; 2] = [&[&a], &[&b]];
let evr = h.expected_variance_reduction(&teams, &target).unwrap();
let curves = h.learning_curves();
let mut curve_bits: u64 = 0;
let mut keys: Vec<&String> = curves.keys().collect();
keys.sort();
for key in keys {
for (t, g) in &curves[key] {
curve_bits ^= (*t as u64).rotate_left(17)
^ g.mu().to_bits().rotate_left(31)
^ g.sigma().to_bits();
}
}
format!(
"post={:016x} evr={:016x} le={:016x} curves={curve_bits:016x}",
posterior.sigma().to_bits(),
evr.to_bits(),
h.log_evidence().to_bits(),
)
}
#[test]
fn results_are_identical_across_processes() {
if env::var(CHILD).is_ok() {
println!("FINGERPRINT {}", fingerprint());
return;
}
let exe = env::current_exe().expect("current exe");
let mut seen: Vec<String> = Vec::new();
for run in 0..RUNS {
let out = Command::new(&exe)
.args([
"results_are_identical_across_processes",
"--exact",
"--nocapture",
])
.env(CHILD, "1")
.output()
.expect("spawn child");
assert!(
out.status.success(),
"child {run} failed: {}",
String::from_utf8_lossy(&out.stderr)
);
let stdout = String::from_utf8_lossy(&out.stdout);
let line = stdout
.lines()
.find_map(|l| l.strip_prefix("FINGERPRINT "))
.unwrap_or_else(|| panic!("child {run} printed no fingerprint:\n{stdout}"))
.to_string();
seen.push(line);
}
let first = &seen[0];
let differing: Vec<&String> = seen.iter().filter(|s| *s != first).collect();
assert!(
differing.is_empty(),
"results differ across processes on identical input.\n {} of {RUNS} runs differed\n \
first: {first}\n differing: {}",
differing.len(),
differing[0]
);
}