trueskill-tt/tests/cross_process_determinism.rs

//! 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, 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<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.joint().unwrap().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
        .joint()
        .unwrap()
        .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]
    );
}