opendp 0.14.2-dev.20260401.2

A library of differential privacy algorithms for the statistical analysis of sensitive private data.
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use super::*;

#[test]
fn test_make_bounded_int_monotonic_sum() -> Fallible<()> {
    let trans = make_bounded_int_monotonic_sum((1i32, 10))?;
    let sum = trans.invoke(&vec![1, 2, 3, 4])?;
    assert_eq!(sum, 10);

    let trans = make_bounded_int_monotonic_sum((1i32, 10))?;
    let sum = trans.invoke(&vec![1, 2, 3, 4])?;
    assert_eq!(sum, 10);

    // should fail under these conditions
    assert!(make_bounded_int_monotonic_sum((-1i32, 1)).is_err());

    Ok(())
}

#[test]
fn test_make_sized_bounded_int_monotonic_sum() -> Fallible<()> {
    let trans = make_sized_bounded_int_monotonic_sum(4, (1i32, 10))?;
    let sum = trans.invoke(&vec![1, 2, 3, 4])?;
    assert_eq!(sum, 10);

    let trans = make_sized_bounded_int_monotonic_sum(4, (1i32, 10))?;
    let sum = trans.invoke(&vec![1, 2, 3, 4])?;
    assert_eq!(sum, 10);

    Ok(())
}