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# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis/
#
# Copyright the Hypothesis Authors.
# Individual contributors are listed in AUTHORS.rst and the git log.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at https://mozilla.org/MPL/2.0/.
import pytest
import hypothesis.strategies as st
from hypothesis import Phase, example, given, settings
from hypothesis.internal.conjecture.dfa.lstar import LStar
@st.composite
def byte_order(draw):
ls = draw(st.permutations(range(256)))
n = draw(st.integers(0, len(ls)))
return ls[:n]
@pytest.mark.skipif(
settings._current_profile == "crosshair",
reason="takes 300s; may get faster after https://github.com/pschanely/CrossHair/issues/332",
)
@example({0}, [1])
@given(st.sets(st.integers(0, 255)), byte_order())
# This test doesn't even use targeting at all, but for some reason the
# pareto optimizer makes it much slower.
@settings(phases=set(settings.default.phases) - {Phase.target})
def test_learning_always_changes_generation(chars, order):
learner = LStar(lambda s: len(s) == 1 and s[0] in chars)
for c in order:
prev = learner.generation
s = bytes([c])
if learner.dfa.matches(s) != learner.member(s):
learner.learn(s)
assert learner.generation > prev
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