|
|
@@ -15,22 +15,24 @@
|
|
|
#include <AK/StringView.h>
|
|
|
#include <AK/Tuple.h>
|
|
|
|
|
|
+#include <math.h>
|
|
|
+
|
|
|
namespace Test {
|
|
|
namespace Randomized {
|
|
|
|
|
|
// Returns a random double value in range 0..1.
|
|
|
-inline double get_random_probability()
|
|
|
+// This is not a generator. It is meant to be used inside RandomnessSource::draw_value().
|
|
|
+// Based on: https://dotat.at/@/2023-06-23-random-double.html
|
|
|
+inline f64 get_random_probability()
|
|
|
{
|
|
|
- static constexpr u32 max_u32 = NumericLimits<u32>::max();
|
|
|
- u32 random_u32 = AK::get_random_uniform(max_u32);
|
|
|
- return static_cast<double>(random_u32) / static_cast<double>(max_u32);
|
|
|
+ return static_cast<f64>(AK::get_random<u64>() >> 11) * 0x1.0p-53;
|
|
|
}
|
|
|
|
|
|
// Generators take random bits from the RandomnessSource and return a value
|
|
|
// back.
|
|
|
//
|
|
|
// Example:
|
|
|
-// - Gen::u32(5,10) --> 9, 7, 5, 10, 8, ...
|
|
|
+// - Gen::number_u64(5,10) --> 9, 7, 5, 10, 8, ...
|
|
|
namespace Gen {
|
|
|
|
|
|
// An unsigned integer generator.
|
|
|
@@ -38,41 +40,41 @@ namespace Gen {
|
|
|
// The minimum value will always be 0.
|
|
|
// The maximum value is given by user in the argument.
|
|
|
//
|
|
|
-// Gen::unsigned_int(10) -> value 5, RandomRun [5]
|
|
|
-// -> value 8, RandomRun [8]
|
|
|
-// etc.
|
|
|
+// Gen::number_u64(10) -> value 5, RandomRun [5]
|
|
|
+// -> value 8, RandomRun [8]
|
|
|
+// etc.
|
|
|
//
|
|
|
// Shrinks towards 0.
|
|
|
-inline u32 unsigned_int(u32 max)
|
|
|
+inline u64 number_u64(u64 max)
|
|
|
{
|
|
|
if (max == 0)
|
|
|
return 0;
|
|
|
|
|
|
- u32 random = Test::randomness_source().draw_value(max, [&]() {
|
|
|
- // `clamp` to guard against integer overflow and calling get_random_uniform(0).
|
|
|
- u32 exclusive_bound = AK::clamp(max + 1, max, NumericLimits<u32>::max());
|
|
|
- return AK::get_random_uniform(exclusive_bound);
|
|
|
+ u64 random = Test::randomness_source().draw_value(max, [&]() {
|
|
|
+ // `clamp` to guard against integer overflow
|
|
|
+ u64 exclusive_bound = AK::clamp(max + 1, max, NumericLimits<u64>::max());
|
|
|
+ return AK::get_random_uniform_64(exclusive_bound);
|
|
|
});
|
|
|
return random;
|
|
|
}
|
|
|
|
|
|
// An unsigned integer generator in a particular range.
|
|
|
//
|
|
|
-// Gen::unsigned_int(3,10) -> value 3, RandomRun [0]
|
|
|
-// -> value 8, RandomRun [5]
|
|
|
-// -> value 10, RandomRun [7]
|
|
|
-// etc.
|
|
|
+// Gen::number_u64(3,10) -> value 3, RandomRun [0]
|
|
|
+// -> value 8, RandomRun [5]
|
|
|
+// -> value 10, RandomRun [7]
|
|
|
+// etc.
|
|
|
//
|
|
|
// In case `min == max`, the RandomRun footprint will be smaller: no randomness
|
|
|
// is needed.
|
|
|
//
|
|
|
-// Gen::unsigned_int(3,3) -> value 3, RandomRun [] (always)
|
|
|
+// Gen::number_u64(3,3) -> value 3, RandomRun [] (always)
|
|
|
//
|
|
|
// Shrinks towards the minimum.
|
|
|
-inline u32 unsigned_int(u32 min, u32 max)
|
|
|
+inline u64 number_u64(u64 min, u64 max)
|
|
|
{
|
|
|
VERIFY(max >= min);
|
|
|
- return unsigned_int(max - min) + min;
|
|
|
+ return number_u64(max - min) + min;
|
|
|
}
|
|
|
|
|
|
// Randomly (uniformly) selects a value out of the given arguments.
|
|
|
@@ -89,7 +91,7 @@ CommonType<Ts...> one_of(Ts... choices)
|
|
|
Vector<CommonType<Ts...>> choices_vec { choices... };
|
|
|
|
|
|
constexpr size_t count = sizeof...(choices);
|
|
|
- size_t i = unsigned_int(count - 1);
|
|
|
+ size_t i = number_u64(count - 1);
|
|
|
return choices_vec[i];
|
|
|
}
|
|
|
|
|
|
@@ -118,16 +120,16 @@ CommonType<Ts...> frequency(Choice<Ts>... choices)
|
|
|
{
|
|
|
Vector<Choice<CommonType<Ts...>>> choices_vec { choices... };
|
|
|
|
|
|
- u32 sum = 0;
|
|
|
+ u64 sum = 0;
|
|
|
for (auto const& choice : choices_vec) {
|
|
|
VERIFY(choice.weight > 0);
|
|
|
- sum += static_cast<u32>(choice.weight);
|
|
|
+ sum += static_cast<u64>(choice.weight);
|
|
|
}
|
|
|
|
|
|
- u32 target = unsigned_int(sum);
|
|
|
+ u64 target = number_u64(sum);
|
|
|
size_t i = 0;
|
|
|
for (auto const& choice : choices_vec) {
|
|
|
- u32 weight = static_cast<u32>(choice.weight);
|
|
|
+ u64 weight = static_cast<u64>(choice.weight);
|
|
|
if (weight >= target) {
|
|
|
return choice.value;
|
|
|
}
|
|
|
@@ -137,46 +139,47 @@ CommonType<Ts...> frequency(Choice<Ts>... choices)
|
|
|
return choices_vec[i - 1].value;
|
|
|
}
|
|
|
|
|
|
-// An unsigned integer generator in the full u32 range.
|
|
|
+// An unsigned integer generator in the full u64 range.
|
|
|
//
|
|
|
-// 8/17 (47%) of the time it will bias towards 8bit numbers,
|
|
|
-// 4/17 (23%) towards 4bit numbers,
|
|
|
-// 2/17 (12%) towards 16bit numbers,
|
|
|
-// 1/17 (6%) towards 32bit numbers,
|
|
|
-// 2/17 (12%) towards edge cases like 0 and NumericLimits::max() of various unsigned int types.
|
|
|
+// Prefers 8bit numbers, then 4bit, 16bit, 32bit and 64bit ones.
|
|
|
+// Around 11% of the time it tries edge cases like 0 and various NumericLimits::max().
|
|
|
//
|
|
|
-// Gen::unsigned_int() -> value 3, RandomRun [0,3]
|
|
|
-// -> value 8, RandomRun [1,8]
|
|
|
-// -> value 100, RandomRun [2,100]
|
|
|
-// -> value 5, RandomRun [3,5]
|
|
|
-// -> value 255, RandomRun [4,1]
|
|
|
-// -> value 65535, RandomRun [4,2]
|
|
|
-// etc.
|
|
|
+// Gen::number_u64() -> value 3, RandomRun [0,3]
|
|
|
+// -> value 8, RandomRun [1,8]
|
|
|
+// -> value 100, RandomRun [2,100]
|
|
|
+// -> value 5, RandomRun [3,5]
|
|
|
+// -> value 255, RandomRun [4,1]
|
|
|
+// -> value 65535, RandomRun [4,2]
|
|
|
+// etc.
|
|
|
//
|
|
|
// Shrinks towards 0.
|
|
|
-inline u32 unsigned_int()
|
|
|
+inline u64 number_u64()
|
|
|
{
|
|
|
- u32 bits = frequency(
|
|
|
+ u64 bits = frequency(
|
|
|
// weight, bits
|
|
|
Choice { 4, 4 },
|
|
|
Choice { 8, 8 },
|
|
|
Choice { 2, 16 },
|
|
|
Choice { 1, 32 },
|
|
|
+ Choice { 1, 64 },
|
|
|
Choice { 2, 0 });
|
|
|
|
|
|
// The special cases go last as they can be the most extreme (large) values.
|
|
|
|
|
|
if (bits == 0) {
|
|
|
- // Special cases, eg. max integers for u8, u16, u32.
|
|
|
+ // Special cases, eg. max integers for u8, u16, u32, u64.
|
|
|
return one_of(
|
|
|
0U,
|
|
|
NumericLimits<u8>::max(),
|
|
|
NumericLimits<u16>::max(),
|
|
|
- NumericLimits<u32>::max());
|
|
|
+ NumericLimits<u32>::max(),
|
|
|
+ NumericLimits<u64>::max());
|
|
|
}
|
|
|
|
|
|
- u32 max = ((u64)1 << bits) - 1;
|
|
|
- return unsigned_int(max);
|
|
|
+ u64 max = bits == 64
|
|
|
+ ? NumericLimits<u64>::max()
|
|
|
+ : ((u64)1 << bits) - 1;
|
|
|
+ return number_u64(max);
|
|
|
}
|
|
|
|
|
|
// A generator returning `true` with the given `probability` (0..1).
|
|
|
@@ -190,15 +193,15 @@ inline u32 unsigned_int()
|
|
|
// -> value true, RandomRun [1]
|
|
|
//
|
|
|
// Shrinks towards false.
|
|
|
-inline bool weighted_boolean(double probability)
|
|
|
+inline bool weighted_boolean(f64 probability)
|
|
|
{
|
|
|
if (probability <= 0)
|
|
|
return false;
|
|
|
if (probability >= 1)
|
|
|
return true;
|
|
|
|
|
|
- u32 random_int = Test::randomness_source().draw_value(1, [&]() {
|
|
|
- double drawn_probability = get_random_probability();
|
|
|
+ u64 random_int = Test::randomness_source().draw_value(1, [&]() {
|
|
|
+ f64 drawn_probability = get_random_probability();
|
|
|
return drawn_probability <= probability ? 1 : 0;
|
|
|
});
|
|
|
bool random_bool = random_int == 1;
|
|
|
@@ -219,7 +222,7 @@ inline bool boolean()
|
|
|
|
|
|
// A vector generator of a random length between the given limits.
|
|
|
//
|
|
|
-// Gen::vector(2,3,[]() { return Gen::unsigned_int(5); })
|
|
|
+// Gen::vector(2,3,[]() { return Gen::number_u64(5); })
|
|
|
// -> value [1,5], RandomRun [1,1,1,5,0]
|
|
|
// -> value [1,5,0], RandomRun [1,1,1,5,1,0,0]
|
|
|
// etc.
|
|
|
@@ -227,7 +230,7 @@ inline bool boolean()
|
|
|
// In case `min == max`, the RandomRun footprint will be smaller, as there will
|
|
|
// be no randomness involved in figuring out the length:
|
|
|
//
|
|
|
-// Gen::vector(3,3,[]() { return Gen::unsigned_int(5); })
|
|
|
+// Gen::vector(3,3,[]() { return Gen::number_u64(5); })
|
|
|
// -> value [1,3], RandomRun [1,3]
|
|
|
// -> value [5,2], RandomRun [5,2]
|
|
|
// etc.
|
|
|
@@ -266,7 +269,7 @@ inline Vector<InvokeResult<Fn>> vector(size_t min, size_t max, Fn item_gen)
|
|
|
++size;
|
|
|
}
|
|
|
|
|
|
- double average = static_cast<double>(min + max) / 2.0;
|
|
|
+ f64 average = static_cast<f64>(min + max) / 2.0;
|
|
|
VERIFY(average > 0);
|
|
|
|
|
|
// A geometric distribution: https://en.wikipedia.org/wiki/Geometric_distribution#Moments_and_cumulants
|
|
|
@@ -279,7 +282,7 @@ inline Vector<InvokeResult<Fn>> vector(size_t min, size_t max, Fn item_gen)
|
|
|
// That gives us `1 - 1/p`. Then, E(X) also contains the final success, so we
|
|
|
// need to say `1 + average` instead of `average`, as it will mean "our X
|
|
|
// items + the final failure that stops the process".
|
|
|
- double probability = 1.0 - 1.0 / (1.0 + average);
|
|
|
+ f64 probability = 1.0 - 1.0 / (1.0 + average);
|
|
|
|
|
|
while (size < max) {
|
|
|
if (weighted_boolean(probability)) {
|
|
|
@@ -295,7 +298,7 @@ inline Vector<InvokeResult<Fn>> vector(size_t min, size_t max, Fn item_gen)
|
|
|
|
|
|
// A vector generator of a given length.
|
|
|
//
|
|
|
-// Gen::vector_of_length(3,[]() { return Gen::unsigned_int(5); })
|
|
|
+// Gen::vector_of_length(3,[]() { return Gen::number_u64(5); })
|
|
|
// -> value [1,5,0], RandomRun [1,1,1,5,1,0,0]
|
|
|
// -> value [2,9,3], RandomRun [1,2,1,9,1,3,0]
|
|
|
// etc.
|
|
|
@@ -312,7 +315,7 @@ inline Vector<InvokeResult<Fn>> vector(size_t length, Fn item_gen)
|
|
|
// If you need a different length, use vector(max,item_gen) or
|
|
|
// vector(min,max,item_gen).
|
|
|
//
|
|
|
-// Gen::vector([]() { return Gen::unsigned_int(5); })
|
|
|
+// Gen::vector([]() { return Gen::number_u64(5); })
|
|
|
// -> value [], RandomRun [0]
|
|
|
// -> value [1], RandomRun [1,1,0]
|
|
|
// -> value [1,5], RandomRun [1,1,1,5,0]
|
|
|
@@ -327,6 +330,118 @@ inline Vector<InvokeResult<Fn>> vector(Fn item_gen)
|
|
|
return vector(0, 32, item_gen);
|
|
|
}
|
|
|
|
|
|
+// A double generator in the [0,1) range.
|
|
|
+//
|
|
|
+// RandomRun footprint: a single number.
|
|
|
+//
|
|
|
+// Shrinks towards 0.
|
|
|
+//
|
|
|
+// Based on: https://dotat.at/@/2023-06-23-random-double.html
|
|
|
+inline f64 percentage()
|
|
|
+{
|
|
|
+ return static_cast<f64>(number_u64() >> 11) * 0x1.0p-53;
|
|
|
+}
|
|
|
+
|
|
|
+// An internal double generator. This one won't make any attempt to shrink nicely.
|
|
|
+// Test writers should use number_f64(f64 min, f64 max) instead.
|
|
|
+inline f64 number_f64_scaled(f64 min, f64 max)
|
|
|
+{
|
|
|
+ VERIFY(max >= min);
|
|
|
+
|
|
|
+ if (min == max)
|
|
|
+ return min;
|
|
|
+
|
|
|
+ f64 p = percentage();
|
|
|
+ return min * (1.0 - p) + max * p;
|
|
|
+}
|
|
|
+
|
|
|
+inline f64 number_f64(f64 min, f64 max)
|
|
|
+{
|
|
|
+ // FIXME: after we figure out how to use frequency() with lambdas,
|
|
|
+ // do edge cases and nicely shrinking float generators here
|
|
|
+
|
|
|
+ return number_f64_scaled(min, max);
|
|
|
+}
|
|
|
+
|
|
|
+inline f64 number_f64()
|
|
|
+{
|
|
|
+ // FIXME: this could be much nicer to the user, at the expense of code complexity
|
|
|
+ // We could follow Hypothesis' lead and remap integers 0..MAXINT to _simple_
|
|
|
+ // floats rather than small floats. Meaning, we would like to prefer integers
|
|
|
+ // over floats with decimal digits, positive numbers over negative numbers etc.
|
|
|
+ // As a result, users would get failures with floats like 0, 1, or 0.5 instead of
|
|
|
+ // ones like 1.175494e-38.
|
|
|
+ // Check the doc comment in Hypothesis: https://github.com/HypothesisWorks/hypothesis/blob/master/hypothesis-python/src/hypothesis/internal/conjecture/floats.py
|
|
|
+
|
|
|
+ return number_f64(NumericLimits<f64>::lowest(), NumericLimits<f64>::max());
|
|
|
+}
|
|
|
+
|
|
|
+// A double generator.
|
|
|
+//
|
|
|
+// The minimum value will always be NumericLimits<f64>::lowest().
|
|
|
+// The maximum value is given by user in the argument.
|
|
|
+//
|
|
|
+// Prefers positive numbers, then negative numbers, then edge cases.
|
|
|
+//
|
|
|
+// Shrinks towards 0.
|
|
|
+inline f64 number_f64(f64 max)
|
|
|
+{
|
|
|
+ // FIXME: after we figure out how to use frequency() with lambdas,
|
|
|
+ // do edge cases and nicely shrinking float generators here
|
|
|
+
|
|
|
+ return number_f64_scaled(NumericLimits<f64>::lowest(), max);
|
|
|
+}
|
|
|
+
|
|
|
+// TODO
|
|
|
+inline u32 number_u32(u32 max)
|
|
|
+{
|
|
|
+ if (max == 0)
|
|
|
+ return 0;
|
|
|
+
|
|
|
+ u32 random = Test::randomness_source().draw_value(max, [&]() {
|
|
|
+ // `clamp` to guard against integer overflow
|
|
|
+ u32 exclusive_bound = AK::clamp(max + 1, max, NumericLimits<u32>::max());
|
|
|
+ return AK::get_random_uniform(exclusive_bound);
|
|
|
+ });
|
|
|
+ return random;
|
|
|
+}
|
|
|
+
|
|
|
+// TODO
|
|
|
+inline u32 number_u32(u32 min, u32 max)
|
|
|
+{
|
|
|
+ VERIFY(max >= min);
|
|
|
+ return number_u32(max - min) + min;
|
|
|
+}
|
|
|
+
|
|
|
+// TODO
|
|
|
+inline u32 number_u32()
|
|
|
+{
|
|
|
+ u32 bits = frequency(
|
|
|
+ // weight, bits
|
|
|
+ Choice { 4, 4 },
|
|
|
+ Choice { 8, 8 },
|
|
|
+ Choice { 2, 16 },
|
|
|
+ Choice { 1, 32 },
|
|
|
+ Choice { 1, 64 },
|
|
|
+ Choice { 2, 0 });
|
|
|
+
|
|
|
+ // The special cases go last as they can be the most extreme (large) values.
|
|
|
+
|
|
|
+ if (bits == 0) {
|
|
|
+ // Special cases, eg. max integers for u8, u16, u32.
|
|
|
+ return one_of(
|
|
|
+ 0U,
|
|
|
+ NumericLimits<u8>::max(),
|
|
|
+ NumericLimits<u16>::max(),
|
|
|
+ NumericLimits<u32>::max());
|
|
|
+ }
|
|
|
+
|
|
|
+ u32 max = bits == 32
|
|
|
+ ? NumericLimits<u32>::max()
|
|
|
+ : ((u32)1 << bits) - 1;
|
|
|
+ return number_u32(max);
|
|
|
+}
|
|
|
+
|
|
|
} // namespace Gen
|
|
|
} // namespace Randomized
|
|
|
} // namespace Test
|
Martin Janiczek