ladybird/Userland/Libraries/LibTest/Randomized/Shrink.h
2023-10-26 17:26:52 -06:00

363 lines
13 KiB
C++

/*
* Copyright (c) 2023, Martin Janiczek <martin@janiczek.cz>
*
* SPDX-License-Identifier: BSD-2-Clause
*/
#pragma once
#include <LibTest/Randomized/Generator.h>
#include <LibTest/Randomized/RandomRun.h>
#include <LibTest/Randomized/RandomnessSource.h>
#include <LibTest/Randomized/ShrinkCommand.h>
#include <LibTest/TestResult.h>
#include <AK/String.h>
namespace Test {
namespace Randomized {
enum class WasImprovement {
Yes,
No,
};
struct ShrinkResult {
WasImprovement was_improvement;
RandomRun run;
};
inline ShrinkResult no_improvement(RandomRun run)
{
return ShrinkResult { WasImprovement::No, run };
}
// When calling keep_if_better we have a new RandomRun that might be better than
// our current_best (which is guaranteed to generate a value and fail the test).
//
// We need to try to generate a value from the new_run and run the test. If the
// generated value fails the test, we say it was an improvement (because of our
// convention for generators that _shorter / smaller RandomRuns lead to simpler
// values_). In all other cases we say it wasn't an improvement.
template<typename Fn>
ShrinkResult keep_if_better(RandomRun const& new_run, RandomRun const& current_best, Fn const& test_function)
{
if (!new_run.is_shortlex_smaller_than(current_best))
// The new run is worse or equal to the current best. Let's not even try!
return no_improvement(current_best);
set_randomness_source(RandomnessSource::recorded(new_run));
set_current_test_result(TestResult::NotRun);
test_function();
if (current_test_result() == TestResult::NotRun) {
set_current_test_result(TestResult::Passed);
}
switch (current_test_result()) {
case TestResult::Failed:
// Our smaller RandomRun resulted in a simpler failing value!
// Let's keep it.
return ShrinkResult { WasImprovement::Yes, new_run };
case TestResult::Passed:
case TestResult::Rejected:
case TestResult::Overrun:
// Passing: We shrank from a failing value to a passing value.
// Rejected: We shrank to value that doesn't get past the ASSUME(...)
// macro.
// Overrun: Generators can't draw enough random bits to generate all
// needed values.
// In all cases: Let's try something else.
return no_improvement(current_best);
case TestResult::NotRun:
default:
// We've literally just set it to Passed if it was NotRun!
VERIFY_NOT_REACHED();
return no_improvement(current_best);
}
}
template<typename Fn, typename UpdateRunFn>
ShrinkResult binary_shrink(u32 orig_low, u32 orig_high, UpdateRunFn update_run, RandomRun const& orig_run, Fn const& test_function)
{
if (orig_low == orig_high) {
return no_improvement(orig_run);
}
RandomRun current_best = orig_run;
u32 low = orig_low;
u32 high = orig_high;
// Let's try with the best case (low = most shrunk) first
RandomRun run_with_low = update_run(low, current_best);
ShrinkResult after_low = keep_if_better(run_with_low, current_best, test_function);
switch (after_low.was_improvement) {
case WasImprovement::Yes:
// We can't do any better
return after_low;
case WasImprovement::No:
break;
}
// Ah well, gotta do some actual work.
//
// We're already guaranteed that `high` makes the test fail. We're trying to
// get as low as `low` (but we know `low` doesn't make the test fail, else
// the `if` above would succeed and return).
//
// Failing value above, passing value below; we try to find the lowest value
// that still fails.
//
// `high` is always guaranteed to fail, `low` is always guaranteed to
// pass/reject/overrun.
ShrinkResult result = after_low;
while (low + 1 < high) {
u32 mid = low + (high - low) / 2;
RandomRun run_with_mid = update_run(mid, current_best);
ShrinkResult after_mid = keep_if_better(run_with_mid, current_best, test_function);
switch (after_mid.was_improvement) {
case WasImprovement::Yes:
high = mid;
break;
case WasImprovement::No:
low = mid;
break;
}
result = after_mid;
current_best = after_mid.run;
}
// did we get below the original `high` at all?
if (current_best.is_shortlex_smaller_than(orig_run)) {
result.was_improvement = WasImprovement::Yes;
} else {
result.was_improvement = WasImprovement::No;
result.run = orig_run;
}
set_current_test_result(TestResult::Failed);
return result;
}
template<typename Fn>
ShrinkResult shrink_zero(ZeroChunk command, RandomRun const& run, Fn const& test_function)
{
RandomRun new_run = run;
size_t end = command.chunk.index + command.chunk.size;
for (size_t i = command.chunk.index; i < end; i++) {
new_run[i] = 0;
}
return keep_if_better(new_run, run, test_function);
}
template<typename Fn>
ShrinkResult shrink_sort(SortChunk command, RandomRun const& run, Fn const& test_function)
{
RandomRun new_run = run.with_sorted(command.chunk);
return keep_if_better(new_run, run, test_function);
}
template<typename Fn>
ShrinkResult shrink_delete(DeleteChunkAndMaybeDecPrevious command, RandomRun const& run, Fn const& test_function)
{
RandomRun run_deleted = run.with_deleted(command.chunk);
// Optional: decrement the previous value. This deals with a non-optimal but
// relatively common generation pattern: run length encoding.
//
// Example: let's say somebody generates lists in this way:
// * generate a random integer >=0 for the length of the list.
// * then, generate that many items
//
// This results in RandomRuns like this one:
// [ 3 (length), 50 (item 1), 21 (item 2), 1 (item 3) ]
//
// Then if we tried deleting the second item without decrementing
// the length, it would fail:
// [ 3 (length), 21 (item 1), 1 (item 2) ] ... runs out of randomness when
// trying to generate the third item!
//
// That's why we try to decrement the number right before the deleted items:
// [ 2 (length), 21 (item 1), 1 (item 2) ] ... generates fine!
//
// Aside: this is why we're generating lists in a different way that plays
// nicer with shrinking: we flip a coin (generate a bool which is `true` with
// a certain probability) to see whether to generate another item. This makes
// items "local" instead of entangled with the non-local length.
if (run_deleted.size() > command.chunk.index - 1 && run_deleted[command.chunk.index - 1] > 0) {
RandomRun run_decremented = run_deleted;
run_decremented[command.chunk.index - 1]--;
return keep_if_better(run_decremented, run, test_function);
}
// Decrementing didn't work; let's try with just the deletion.
return keep_if_better(run_deleted, run, test_function);
}
template<typename Fn>
ShrinkResult shrink_minimize(MinimizeChoice command, RandomRun const& run, Fn const& test_function)
{
u32 value = run[command.index];
// We can't minimize 0! Already the best possible case.
if (value == 0) {
return no_improvement(run);
}
return binary_shrink(
0,
value,
[&](u32 new_value, RandomRun const& run) {
RandomRun copied_run = run;
copied_run[command.index] = new_value;
return copied_run;
},
run,
test_function);
}
template<typename Fn>
ShrinkResult shrink_swap_chunk(SwapChunkWithNeighbour command, RandomRun const& run, Fn const& test_function)
{
RandomRun run_swapped = run;
// The safety of these swaps was guaranteed by has_a_chance() earlier
for (size_t i = command.chunk.index; i < command.chunk.index + command.chunk.size; ++i) {
AK::swap(run_swapped[i], run_swapped[i + command.chunk.size]);
}
return keep_if_better(run_swapped, run, test_function);
}
template<typename Fn>
ShrinkResult shrink_redistribute(RedistributeChoicesAndMaybeInc command, RandomRun const& run, Fn const& test_function)
{
RandomRun current_best = run;
RandomRun run_after_swap = current_best;
// First try to swap them if they're out of order.
if (run_after_swap[command.left_index] > run_after_swap[command.right_index])
AK::swap(run_after_swap[command.left_index], run_after_swap[command.right_index]);
ShrinkResult after_swap = keep_if_better(run_after_swap, current_best, test_function);
current_best = after_swap.run;
u32 constant_sum = current_best[command.right_index] + current_best[command.left_index];
ShrinkResult after_redistribute = binary_shrink(
0,
current_best[command.left_index],
[&](u32 new_value, RandomRun const& run) {
RandomRun copied_run = run;
copied_run[command.left_index] = new_value;
copied_run[command.right_index] = constant_sum - new_value;
return copied_run;
},
current_best,
test_function);
switch (after_redistribute.was_improvement) {
case WasImprovement::Yes:
return after_redistribute;
break;
case WasImprovement::No:
break;
}
// If the redistribute failed, this can sometimes signal that a value needs
// to fall into the next `int_frequency` bucket. We can try one last-ditch
// attempt and see if incrementing the number right before the right index
// helps.
if (command.left_index == command.right_index - 1) {
// There's no "bucket index" between the left and right index.
// Let's not even try.
return after_swap;
}
RandomRun run_after_increment = after_redistribute.run;
++run_after_increment[command.right_index - 1];
ShrinkResult after_inc_redistribute = binary_shrink(
0,
current_best[command.left_index],
[&](u32 new_value, RandomRun const& run) {
RandomRun copied_run = run;
copied_run[command.left_index] = new_value;
copied_run[command.right_index] = constant_sum - new_value;
return copied_run;
},
current_best,
test_function);
switch (after_inc_redistribute.was_improvement) {
case WasImprovement::Yes:
return after_inc_redistribute;
break;
case WasImprovement::No:
break;
}
return after_swap;
}
template<typename Fn>
ShrinkResult shrink_with_command(ShrinkCommand command, RandomRun const& run, Fn const& test_function)
{
return command.visit(
[&](ZeroChunk c) { return shrink_zero(c, run, test_function); },
[&](SortChunk c) { return shrink_sort(c, run, test_function); },
[&](DeleteChunkAndMaybeDecPrevious c) { return shrink_delete(c, run, test_function); },
[&](MinimizeChoice c) { return shrink_minimize(c, run, test_function); },
[&](RedistributeChoicesAndMaybeInc c) { return shrink_redistribute(c, run, test_function); },
[&](SwapChunkWithNeighbour c) { return shrink_swap_chunk(c, run, test_function); });
}
template<typename Fn>
RandomRun shrink_once(RandomRun const& run, Fn const& test_function)
{
RandomRun current = run;
auto commands = ShrinkCommand::for_run(run);
for (ShrinkCommand command : commands) {
// We're keeping the list of ShrinkCommands we generated from the initial
// RandomRun, as we try to shrink our current best RandomRun.
//
// That means some of the ShrinkCommands might have no chance to
// successfully finish (eg. the command's chunk is out of bounds of the
// run). That's what we check here and based on what we skip those
// commands early.
//
// In the next `shrink -> shrink_once` loop we'll generate a better set
// of commands, more tailored to the current best RandomRun.
if (!command.has_a_chance(current)) {
continue;
}
ShrinkResult result = shrink_with_command(command, current, test_function);
switch (result.was_improvement) {
case WasImprovement::Yes:
current = result.run;
break;
case WasImprovement::No:
break;
}
}
return current;
}
template<typename Fn>
RandomRun shrink(RandomRun const& first_failure, Fn const& test_function)
{
if (first_failure.is_empty()) {
// We can't do any better
return first_failure;
}
RandomRun next = first_failure;
RandomRun current;
do {
current = next;
next = shrink_once(current, test_function);
} while (next.is_shortlex_smaller_than(current));
set_current_test_result(TestResult::Failed);
return next;
}
} // namespace Randomized
} // namespace Test