//! 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 `builtins-test/tests/misc.rs` for //! an example. //! //! Some floating point tests are disabled for specific architectures, because they do not have //! correct rounding. #![no_std] #![cfg_attr(f128_enabled, feature(f128))] #![cfg_attr(f16_enabled, feature(f16))] pub mod bench; extern crate alloc; use compiler_builtins::float::Float; use compiler_builtins::int::{Int, MinInt}; use rand_xoshiro::Xoshiro128StarStar; use rand_xoshiro::rand_core::{RngCore, SeedableRng}; /// 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 }; /// 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(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(); // 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, } // 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, } } // 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 } } }; } /// 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(n: u32, mut f: F) where ::UnsignedInt: Int, { // edge case tester. Calls `f` 210 times for u128. // zero gets skipped by the loop f(I::ZERO); edge_cases!(I, case, { f(case); }); // random fuzzer let mut rng = Xoshiro128StarStar::seed_from_u64(0); let mut x: I = MinInt::ZERO; for _ in 0..n { fuzz_step(&mut rng, &mut x); f(x) } } /// The same as `fuzz`, except `f` has two inputs. pub fn fuzz_2(n: u32, f: F) where ::UnsignedInt: Int, { // 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); }) }); // 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) } } /// Tester for shift functions pub fn fuzz_shift(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 = MinInt::ZERO; for i in 0..I::FUZZ_NUM { fuzz_step(&mut rng, &mut x); f(x, MinInt::ZERO); f(x, I::FUZZ_LENGTHS[i] as u32); } } fn fuzz_float_step(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 // sign bit fuzzing let sign = (rng32 & 1) != 0; // exponent fuzzing. Only 4 bits for the selector needed. let ones = (F::Int::ONE << F::EXP_BITS) - F::Int::ONE; let r0 = (rng32 >> 1) % F::EXP_BITS; let r1 = (rng32 >> 5) % F::EXP_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::EXP_BITS - r1)) & ones }; let mut exp = (f.to_bits() & F::EXP_MASK) >> F::SIG_BITS; match (rng32 >> 9) % 4 { 0 => exp |= mask, 1 => exp &= mask, _ => exp ^= mask, } // significand fuzzing let mut sig = f.to_bits() & F::SIG_MASK; fuzz_step(rng, &mut sig); sig &= F::SIG_MASK; *f = F::from_parts(sign, exp, sig); } macro_rules! float_edge_cases { ($F:ident, $case:ident, $inner:block) => { for exponent in [ F::Int::ZERO, F::Int::ONE, F::Int::ONE << (F::EXP_BITS / 2), (F::Int::ONE << (F::EXP_BITS - 1)) - F::Int::ONE, F::Int::ONE << (F::EXP_BITS - 1), (F::Int::ONE << (F::EXP_BITS - 1)) + F::Int::ONE, (F::Int::ONE << F::EXP_BITS) - F::Int::ONE, ] .iter() { for significand in [ F::Int::ZERO, F::Int::ONE, F::Int::ONE << (F::SIG_BITS / 2), (F::Int::ONE << (F::SIG_BITS - 1)) - F::Int::ONE, F::Int::ONE << (F::SIG_BITS - 1), (F::Int::ONE << (F::SIG_BITS - 1)) + F::Int::ONE, (F::Int::ONE << F::SIG_BITS) - F::Int::ONE, ] .iter() { for sign in [false, true].iter() { let $case = F::from_parts(*sign, *exponent, *significand); $inner } } } }; } pub fn fuzz_float(n: u32, f: E) { float_edge_cases!(F, case, { f(case); }); // 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); } } pub fn fuzz_float_2(n: u32, f: E) { float_edge_cases!(F, case0, { float_edge_cases!(F, case1, { f(case0, case1); }); }); // 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) } } /// Perform an operation using builtin types if available, falling back to apfloat if not. #[macro_export] macro_rules! apfloat_fallback { ( $float_ty:ty, // Type name in `rustc_apfloat::ieee`. Not a full path, it automatically gets the prefix. $apfloat_ty:ident, // Cfg expression for when builtin system operations should be used $sys_available:meta, // The expression to run. This expression may use `FloatTy` for its signature. // Optionally, the final conversion back to a float can be suppressed using // `=> no_convert` (for e.g. operations that return a bool). // // If the apfloat needs a different operation, it can be provided here. $op:expr $(=> $convert:ident)? $(; $apfloat_op:expr)?, // Arguments that get passed to `$op` after converting to a float $($arg:expr),+ $(,)? ) => {{ #[cfg($sys_available)] let ret = { type FloatTy = $float_ty; $op( $($arg),+ ) }; #[cfg(not($sys_available))] let ret = { use rustc_apfloat::Float; type FloatTy = rustc_apfloat::ieee::$apfloat_ty; apfloat_fallback!(@inner fty: $float_ty, // Apply a conversion to `FloatTy` to each arg, then pass all args to `$op` op_res: $op( $(FloatTy::from_bits($arg.to_bits().into())),+ ), $(apfloat_op: $apfloat_op, )? $(conv_opts: $convert,)? args: $($arg),+ ) }; ret }}; // Operations that do not need converting back to a float (@inner fty: $float_ty:ty, op_res: $val:expr, conv_opts: no_convert, args: $($_arg:expr),+) => { $val }; // Some apfloat operations return a `StatusAnd` that we need to extract the value from. This // is the default. (@inner fty: $float_ty:ty, op_res: $val:expr, args: $($_arg:expr),+) => {{ // ignore the status, just get the value let unwrapped = $val.value; <$float_ty>::from_bits(FloatTy::to_bits(unwrapped).try_into().unwrap()) }}; // This is the case where we can't use the same expression for the default builtin and // nonstandard apfloat fallback (e.g. `as` casts in std are normal functions in apfloat, so // two separate expressions must be specified. (@inner fty: $float_ty:ty, op_res: $_val:expr, apfloat_op: $apfloat_op:expr, args: $($arg:expr),+ ) => {{ $apfloat_op($($arg),+) }}; }