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adds testing for almost every numerical intrinsic
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//! This crate is for integration testing and fuzz testing of functions in `compiler-builtins`. This | ||
//! includes publicly documented intrinsics and some internal alternative implementation functions | ||
//! such as `usize_leading_zeros_riscv` (which are tested because they are configured for | ||
//! architectures not tested by the CI). | ||
//! | ||
//! The general idea is to use a combination of edge case testing and randomized fuzz testing. The | ||
//! edge case testing is crucial for checking cases like where both inputs are equal or equal to | ||
//! special values such as `i128::MIN`, which is unlikely for the random fuzzer by itself to | ||
//! encounter. The randomized fuzz testing is specially designed to cover wide swaths of search | ||
//! space in as few iterations as possible. See `fuzz_values` in `testcrate/tests/misc.rs` for an | ||
//! example. | ||
//! | ||
//! Some floating point tests are disabled for specific architectures, because they do not have | ||
//! correct rounding. | ||
#![no_std] | ||
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use compiler_builtins::float::Float; | ||
use compiler_builtins::int::Int; | ||
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use rand_xoshiro::rand_core::{RngCore, SeedableRng}; | ||
use rand_xoshiro::Xoshiro128StarStar; | ||
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/// Sets the number of fuzz iterations run for most tests. In practice, the vast majority of bugs | ||
/// are caught by the edge case testers. Most of the remaining bugs triggered by more complex | ||
/// sequences are caught well within 10_000 fuzz iterations. For classes of algorithms like division | ||
/// that are vulnerable to rare edge cases, we want 1_000_000 iterations to be more confident. In | ||
/// practical CI, however, we only want to run the more strenuous test once to catch algorithmic | ||
/// level bugs, and run the 10_000 iteration test on most targets. Target-dependent bugs are likely | ||
/// to involve miscompilation and misconfiguration that is likely to break algorithms in quickly | ||
/// caught ways. We choose to configure `N = 1_000_000` iterations for `x86_64` targets (and if | ||
/// debug assertions are disabled. Tests without `--release` would take too long) which are likely | ||
/// to have fast hardware, and run `N = 10_000` for all other targets. | ||
pub const N: u32 = if cfg!(target_arch = "x86_64") && !cfg!(debug_assertions) { | ||
1_000_000 | ||
} else { | ||
10_000 | ||
}; | ||
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/// Random fuzzing step. When run several times, it results in excellent fuzzing entropy such as: | ||
/// 11110101010101011110111110011111 | ||
/// 10110101010100001011101011001010 | ||
/// 1000000000000000 | ||
/// 10000000000000110111110000001010 | ||
/// 1111011111111101010101111110101 | ||
/// 101111111110100000000101000000 | ||
/// 10000000110100000000100010101 | ||
/// 1010101010101000 | ||
fn fuzz_step<I: Int>(rng: &mut Xoshiro128StarStar, x: &mut I) { | ||
let ones = !I::ZERO; | ||
let bit_indexing_mask: u32 = I::BITS - 1; | ||
// It happens that all the RNG we need can come from one call. 7 bits are needed to index a | ||
// worst case 128 bit integer, and there are 4 indexes that need to be made plus 4 bits for | ||
// selecting operations | ||
let rng32 = rng.next_u32(); | ||
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// Randomly OR, AND, and XOR randomly sized and shifted continuous strings of | ||
// ones with `lhs` and `rhs`. | ||
let r0 = bit_indexing_mask & rng32; | ||
let r1 = bit_indexing_mask & (rng32 >> 7); | ||
let mask = ones.wrapping_shl(r0).rotate_left(r1); | ||
match (rng32 >> 14) % 4 { | ||
0 => *x |= mask, | ||
1 => *x &= mask, | ||
// both 2 and 3 to make XORs as common as ORs and ANDs combined | ||
_ => *x ^= mask, | ||
} | ||
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// Alternating ones and zeros (e.x. 0b1010101010101010). This catches second-order | ||
// problems that might occur for algorithms with two modes of operation (potentially | ||
// there is some invariant that can be broken and maintained via alternating between modes, | ||
// breaking the algorithm when it reaches the end). | ||
let mut alt_ones = I::ONE; | ||
for _ in 0..(I::BITS / 2) { | ||
alt_ones <<= 2; | ||
alt_ones |= I::ONE; | ||
} | ||
let r0 = bit_indexing_mask & (rng32 >> 16); | ||
let r1 = bit_indexing_mask & (rng32 >> 23); | ||
let mask = alt_ones.wrapping_shl(r0).rotate_left(r1); | ||
match rng32 >> 30 { | ||
0 => *x |= mask, | ||
1 => *x &= mask, | ||
_ => *x ^= mask, | ||
} | ||
} | ||
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// We need macros like this, because `#![no_std]` prevents us from using iterators | ||
macro_rules! edge_cases { | ||
($I:ident, $case:ident, $inner:block) => { | ||
for i0 in 0..$I::FUZZ_NUM { | ||
let mask_lo = (!$I::UnsignedInt::ZERO).wrapping_shr($I::FUZZ_LENGTHS[i0] as u32); | ||
for i1 in i0..I::FUZZ_NUM { | ||
let mask_hi = | ||
(!$I::UnsignedInt::ZERO).wrapping_shl($I::FUZZ_LENGTHS[i1 - i0] as u32); | ||
let $case = I::from_unsigned(mask_lo & mask_hi); | ||
$inner | ||
} | ||
} | ||
}; | ||
} | ||
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/// Feeds a series of fuzzing inputs to `f`. The fuzzer first uses an algorithm designed to find | ||
/// edge cases, followed by a more random fuzzer that runs `n` times. | ||
pub fn fuzz<I: Int, F: FnMut(I)>(n: u32, mut f: F) { | ||
// edge case tester. Calls `f` 210 times for u128. | ||
// zero gets skipped by the loop | ||
f(I::ZERO); | ||
edge_cases!(I, case, { | ||
f(case); | ||
}); | ||
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// random fuzzer | ||
let mut rng = Xoshiro128StarStar::seed_from_u64(0); | ||
let mut x: I = Int::ZERO; | ||
for _ in 0..n { | ||
fuzz_step(&mut rng, &mut x); | ||
f(x) | ||
} | ||
} | ||
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/// The same as `fuzz`, except `f` has two inputs. | ||
pub fn fuzz_2<I: Int, F: Fn(I, I)>(n: u32, f: F) { | ||
// Check cases where the first and second inputs are zero. Both call `f` 210 times for `u128`. | ||
edge_cases!(I, case, { | ||
f(I::ZERO, case); | ||
}); | ||
edge_cases!(I, case, { | ||
f(case, I::ZERO); | ||
}); | ||
// Nested edge tester. Calls `f` 44100 times for `u128`. | ||
edge_cases!(I, case0, { | ||
edge_cases!(I, case1, { | ||
f(case0, case1); | ||
}) | ||
}); | ||
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// random fuzzer | ||
let mut rng = Xoshiro128StarStar::seed_from_u64(0); | ||
let mut x: I = I::ZERO; | ||
let mut y: I = I::ZERO; | ||
for _ in 0..n { | ||
fuzz_step(&mut rng, &mut x); | ||
fuzz_step(&mut rng, &mut y); | ||
f(x, y) | ||
} | ||
} | ||
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/// Tester for shift functions | ||
pub fn fuzz_shift<I: Int, F: Fn(I, u32)>(f: F) { | ||
// Shift functions are very simple and do not need anything other than shifting a small | ||
// set of random patterns for every fuzz length. | ||
let mut rng = Xoshiro128StarStar::seed_from_u64(0); | ||
let mut x: I = Int::ZERO; | ||
for i in 0..I::FUZZ_NUM { | ||
fuzz_step(&mut rng, &mut x); | ||
f(x, Int::ZERO); | ||
f(x, I::FUZZ_LENGTHS[i] as u32); | ||
} | ||
} | ||
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fn fuzz_float_step<F: Float>(rng: &mut Xoshiro128StarStar, f: &mut F) { | ||
let rng32 = rng.next_u32(); | ||
// we need to fuzz the different parts of the float separately, because the masking on larger | ||
// significands will tend to set the exponent to all ones or all zeros frequently | ||
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// sign bit fuzzing | ||
let sign = (rng32 & 1) != 0; | ||
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// exponent fuzzing. Only 4 bits for the selector needed. | ||
let ones = (F::Int::ONE << F::EXPONENT_BITS) - F::Int::ONE; | ||
let r0 = (rng32 >> 1) % F::EXPONENT_BITS; | ||
let r1 = (rng32 >> 5) % F::EXPONENT_BITS; | ||
// custom rotate shift. Note that `F::Int` is unsigned, so we can shift right without smearing | ||
// the sign bit. | ||
let mask = if r1 == 0 { | ||
ones.wrapping_shr(r0) | ||
} else { | ||
let tmp = ones.wrapping_shr(r0); | ||
(tmp.wrapping_shl(r1) | tmp.wrapping_shr(F::EXPONENT_BITS - r1)) & ones | ||
}; | ||
let mut exp = (f.repr() & F::EXPONENT_MASK) >> F::SIGNIFICAND_BITS; | ||
match (rng32 >> 9) % 4 { | ||
0 => exp |= mask, | ||
1 => exp &= mask, | ||
_ => exp ^= mask, | ||
} | ||
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// significand fuzzing | ||
let mut sig = f.repr() & F::SIGNIFICAND_MASK; | ||
fuzz_step(rng, &mut sig); | ||
sig &= F::SIGNIFICAND_MASK; | ||
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*f = F::from_parts(sign, exp, sig); | ||
} | ||
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macro_rules! float_edge_cases { | ||
($F:ident, $case:ident, $inner:block) => { | ||
for exponent in [ | ||
F::Int::ZERO, | ||
F::Int::ONE, | ||
F::Int::ONE << (F::EXPONENT_BITS / 2), | ||
(F::Int::ONE << (F::EXPONENT_BITS - 1)) - F::Int::ONE, | ||
F::Int::ONE << (F::EXPONENT_BITS - 1), | ||
(F::Int::ONE << (F::EXPONENT_BITS - 1)) + F::Int::ONE, | ||
(F::Int::ONE << F::EXPONENT_BITS) - F::Int::ONE, | ||
] | ||
.iter() | ||
{ | ||
for significand in [ | ||
F::Int::ZERO, | ||
F::Int::ONE, | ||
F::Int::ONE << (F::SIGNIFICAND_BITS / 2), | ||
(F::Int::ONE << (F::SIGNIFICAND_BITS - 1)) - F::Int::ONE, | ||
F::Int::ONE << (F::SIGNIFICAND_BITS - 1), | ||
(F::Int::ONE << (F::SIGNIFICAND_BITS - 1)) + F::Int::ONE, | ||
(F::Int::ONE << F::SIGNIFICAND_BITS) - F::Int::ONE, | ||
] | ||
.iter() | ||
{ | ||
for sign in [false, true].iter() { | ||
let $case = F::from_parts(*sign, *exponent, *significand); | ||
$inner | ||
} | ||
} | ||
} | ||
}; | ||
} | ||
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pub fn fuzz_float<F: Float, E: Fn(F)>(n: u32, f: E) { | ||
float_edge_cases!(F, case, { | ||
f(case); | ||
}); | ||
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// random fuzzer | ||
let mut rng = Xoshiro128StarStar::seed_from_u64(0); | ||
let mut x = F::ZERO; | ||
for _ in 0..n { | ||
fuzz_float_step(&mut rng, &mut x); | ||
f(x); | ||
} | ||
} | ||
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pub fn fuzz_float_2<F: Float, E: Fn(F, F)>(n: u32, f: E) { | ||
float_edge_cases!(F, case0, { | ||
float_edge_cases!(F, case1, { | ||
f(case0, case1); | ||
}); | ||
}); | ||
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// random fuzzer | ||
let mut rng = Xoshiro128StarStar::seed_from_u64(0); | ||
let mut x = F::ZERO; | ||
let mut y = F::ZERO; | ||
for _ in 0..n { | ||
fuzz_float_step(&mut rng, &mut x); | ||
fuzz_float_step(&mut rng, &mut y); | ||
f(x, y) | ||
} | ||
} |
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