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483 lines
12 KiB
483 lines
12 KiB
require "test_helper"
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class Minitest::ThesisTest < Minitest::Thesis
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class Failure < StandardError; end
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def test_finds_small_list
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(0...10).each do |seed|
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("finds_small_list", database: {}, random: Random.new(seed)) do |test_case|
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ls = test_case.any(lists(integers(0, 10_000)))
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assert ls.sum <= 1_000
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end
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end
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end
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assert_equal <<~OUT, out
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any(lists(integers(0, 10000))): [1001]
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OUT
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end
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end
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# Minithesis can't really handle shrinking arbitrary monadic bind, but length
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# parameters are a common case of monadic bind that it has a little bit of
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# special casing for. This test ensures that that special casing works.
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#
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# The problem is that if you generate a list by drawing a length and then
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# drawing that many elements, you can end up with something like ``[1001, 0,
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# 0]`` then deleting those zeroes in the middle is a pain. minithesis will
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# solve this by first sorting those elements, so that we have ``[0, 0,
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# 1001]``, and then lowering the length by two, turning it into ``[1001]`` as
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# desired.
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def test_finds_small_list_even_with_bad_lists
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bad_list = Possibility.new("bad_list") {|tc|
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n = tc.choice(10)
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Array.new(n) { tc.choice(10_000) }
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}
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(0...10).each do |seed|
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("finds_small_list_even_with_bad_lists", database: {}, random: Random.new(seed)) do |test_case|
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ls = test_case.any(bad_list)
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assert ls.sum <= 1_000
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end
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end
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end
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assert_equal <<~OUT, out
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any(bad_list): [1001]
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OUT
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end
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end
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def test_reduces_additive_pairs
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("reduces_additive_pairs", database: {}, max_examples: 10_000) do |test_case|
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m = test_case.choice(1000)
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n = test_case.choice(1000)
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assert m + n <= 1000
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end
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end
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end
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assert_equal <<~OUT, out
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choice(1000): 1
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choice(1000): 1000
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OUT
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end
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def test_reuses_results_from_the_database
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Dir.mktmpdir do |tmpdir|
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db = DirectoryDb.new(tmpdir)
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count = 0
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run = -> {
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assert_raises(Minitest::Assertion) do
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run_test("reuses_results_from_the_database", database: db, quiet: true) do |test_case|
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count += 1
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assert test_case.choice(10_000) < 10
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end
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end
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}
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run.()
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assert_equal 1, Dir.children(tmpdir).length
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prev_count = count
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run.()
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assert_equal 1, Dir.children(tmpdir).length
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assert_equal prev_count + 2, count
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end
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end
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def test_test_cases_satisfy_preconditions
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run_test("test_cases_satisfy_preconditions", database: {}) do |test_case|
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n = test_case.choice(10)
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test_case.assume(n != 0)
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refute_equal 0, n
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end
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end
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def test_error_on_too_strict_precondition
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assert_raises(Unsatisfiable) do
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run_test("error_on_too_strict_precondition", database: {}) do |test_case|
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n = test_case.choice(10)
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test_case.reject
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end
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end
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end
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def test_error_on_unbounded_test_function
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orig_buffer_size = BUFFER_SIZE
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suppress_warnings do
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Minitest::Thesis.const_set(:BUFFER_SIZE, 10)
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end
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assert_raises(Unsatisfiable) do
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run_test("error_on_unbounded_test_function", database: {}, max_examples: 5) do |test_case|
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loop do
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test_case.choice(10)
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end
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end
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end
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ensure
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suppress_warnings do
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Minitest::Thesis.const_set(:BUFFER_SIZE, orig_buffer_size)
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end
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end
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def test_function_cache
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tf = ->(tc) do
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tc.mark_status(Status::INTERESTING) if tc.choice(1_000) >= 200
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tc.reject if tc.choice(1).zero?
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end
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state = TestingState.new(random: Random.new(0), test_function: tf, max_examples: 100)
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cache = CachedTestFunction.new {|tc| state.test_function(tc) }
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assert_equal Status::VALID, cache.([1, 1])
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assert_equal Status::OVERRUN, cache.([1])
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assert_equal Status::INTERESTING, cache.([1_000])
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assert_equal Status::INTERESTING, cache.([1_000])
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assert_equal Status::INTERESTING, cache.([1_000, 1])
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assert_equal 2, state.calls
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end
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# Targeting has a number of places it checks for whether we've exceeded the
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# generation limits. This makes sure we've checked them all.
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def test_max_examples_is_not_exceeded
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(1...100).each do |max_examples|
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calls = 0
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run_test(
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"max_examples_is_not_exceeded",
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database: {},
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random: Random.new(0),
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max_examples:,
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) do |tc|
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m = 10000
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n = tc.choice(m)
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calls += 1
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tc.target(n * (m - n))
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end
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assert_equal max_examples, calls
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end
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end
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# Targeting has a number of places it checks for whether we've exceeded the
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# generation limits. This makes sure we've checked them all.
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def test_finds_a_local_maximum
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(0...100).each do |seed|
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assert_raises(Minitest::Assertion) do
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run_test(
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"finds_a_local_maximum",
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database: {},
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random: Random.new(seed),
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max_examples: 200,
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quiet: true
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) do |tc|
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m = tc.choice(1000)
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n = tc.choice(1000)
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score = -((m - 500) ** 2 + (n - 500) ** 2)
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tc.target(score)
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assert m != 500 || n != 500
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end
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end
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end
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end
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def test_can_target_a_score_upwards_to_interesting
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("can_target_a_score_upwards_to_interesting", database: {}, max_examples: 1000) do |test_case|
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n = test_case.choice(1000)
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m = test_case.choice(1000)
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score = n + m
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test_case.target(score)
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assert score < 2000
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end
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end
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end
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assert_equal <<~OUT, out
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choice(1000): 1000
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choice(1000): 1000
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OUT
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end
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def test_can_target_a_score_upwards_without_failing
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max_score = 0
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run_test("can_target_a_score_upwards_without_failing", database: {}, max_examples: 1000) do |test_case|
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n = test_case.choice(1000)
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m = test_case.choice(1000)
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score = n + m
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test_case.target(score)
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max_score = [score, max_score].max
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end
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assert_equal 2000, max_score
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end
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def test_targeting_when_most_do_not_benefit
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big = 10_000
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("targeting_when_most_do_not_benefit", database: {}, max_examples: 1000) do |test_case|
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test_case.choice(1000)
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test_case.choice(1000)
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score = test_case.choice(big)
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test_case.target(score)
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assert score < big
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end
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end
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end
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assert_equal <<~OUT, out
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choice(1000): 0
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choice(1000): 0
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choice(#{big}): #{big}
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OUT
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end
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def test_can_target_a_score_downwards
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("can_target_a_score_downwards", database: {}, max_examples: 1000) do |test_case|
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n = test_case.choice(1000)
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m = test_case.choice(1000)
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score = n + m
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test_case.target(-score)
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assert score.positive?
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end
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end
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end
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assert_equal <<~OUT, out
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choice(1000): 0
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choice(1000): 0
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OUT
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end
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def test_prints_a_top_level_weighted
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("prints_a_top_level_weighted", database: {}, max_examples: 1000) do |test_case|
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assert test_case.weighted(0.5).nonzero?
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end
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end
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end
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assert_equal <<~OUT, out
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weighted(0.5): 0
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OUT
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end
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def test_errors_when_using_frozen
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tc = TestCase.for_choices([0])
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tc.status = Status::VALID
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assert_raises(Frozen) do
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tc.mark_status(Status::INTERESTING)
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end
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assert_raises(Frozen) do
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tc.choice(10)
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end
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assert_raises(Frozen) do
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tc.forced_choice(10)
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end
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end
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def test_errors_on_too_large_choice
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tc = TestCase.for_choices([0])
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assert_raises(RangeError) do
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tc.choice(2 ** 64)
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end
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end
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def test_can_choose_full_64_bits
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run_test("can_choose_full_64_bits", database: {}) do |tc|
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tc.choice(2 ** 64 - 1)
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end
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end
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def test_mapped_possibility
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run_test("mapped_possibility", database: {}) do |tc|
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n = tc.any(integers(0, 5).map {|n| n * 2 })
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assert n.even?
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end
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end
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def test_selected_possibility
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run_test("selected_possibility", database: {}) do |tc|
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n = tc.any(
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integers(0, 5)
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.satisfying(&:even?)
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)
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assert n.even?
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end
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end
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def test_bound_possibility
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run_test("bound_possibility", database: {}) do |tc|
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m, n = tc.any(
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integers(0, 5).bind {|m| tuples(just(m), integers(m, m + 10)) }
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)
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assert (m..m+10).cover?(n)
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end
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end
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def test_cannot_witness_nothing
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assert_raises(Unsatisfiable) do
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run_test("cannot_witness_nothing", database: {}) do |tc|
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tc.any(nothing)
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end
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end
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end
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def test_cannot_witness_empty_mix_of
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assert_raises(Unsatisfiable) do
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run_test("cannot_witness_empty_mix_of", database: {}) do |tc|
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tc.any(mix_of)
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end
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end
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end
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def test_can_draw_mixture
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run_test("can_draw_mixture", database: {}) do |tc|
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m = tc.any(mix_of(integers(-5, 0), integers(2, 5)))
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assert (-5..5).cover?(m)
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refute_equal 1, m
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end
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end
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# This test is very hard to trigger without targeting, and targeting will
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# tend to overshoot the score, so we will see multiple interesting test cases
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# before shrinking.
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def test_target_and_reduce
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out, _ = capture_io do
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assert_raises(Minitest::Assertion) do
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run_test("target_and_reduce", database: {}) do |tc|
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m = tc.choice(100_000)
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tc.target(m)
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assert m <= 99_900
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end
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end
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end
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assert_equal <<~OUT, out
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choice(100000): 99901
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OUT
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end
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def test_impossible_weighted
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assert_raises(Failure) do
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run_test("impossible_weighted", database: {}, quiet: true) do |tc|
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tc.choice(1)
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10.times do
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assert false unless tc.weighted(0.0).zero?
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end
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raise Failure if tc.choice(1).zero?
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end
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end
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end
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def test_guaranteed_weighted
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assert_raises(Failure) do
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run_test("guaranteed_weighted", database: {}, quiet: true) do |tc|
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if tc.weighted(1.0).nonzero?
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tc.choice(1)
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raise Failure
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else
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assert false
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end
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end
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end
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end
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def test_size_bounds_on_list
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run_test("size_bounds_on_list", database: {}) do |tc|
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ls = tc.any(lists(integers(0, 10), min_size: 1, max_size: 3))
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assert (1..3).cover?(ls.length)
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end
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end
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def test_forced_choice_bounds
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assert_raises(RangeError) do
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run_test("forced_choice_bounds", database: {}) do |tc|
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tc.forced_choice(2 ** 64)
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end
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end
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end
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def test_failure_from_hypothesis_1
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assert_raises(Failure) do
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run_test("failure_from_hypothesis_1", database: {}, random: Random.new(100), max_examples: 1000, quiet: true) do |tc|
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n1 = tc.weighted(0.0)
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if n1.zero?
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n2 = tc.choice(511)
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if n2 == 112
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n3 = tc.choice(511)
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if n3 == 124
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raise Failure
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elsif n3 == 93
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raise Failure
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else
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tc.mark_status(Status::INVALID)
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end
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elsif n2 == 93
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raise Failure
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else
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tc.mark_status(Status::INVALID)
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end
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end
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end
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end
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end
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def test_failure_from_hypothesis_2
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assert_raises(Failure) do
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run_test("failure_from_hypothesis_2", database: {}, random: Random.new(0), max_examples: 1000, quiet: true) do |tc|
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n1 = tc.choice(6)
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if n1 == 6
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n2 = tc.weighted(0.0)
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if n2.zero?
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raise Failure
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end
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elsif n1 == 4
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n3 = tc.choice(0)
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if n3 == 0
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raise Failure
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else
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tc.mark_status(Status::INVALID)
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end
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elsif n1 == 2
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raise Failure
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else
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tc.mark_status(Status::INVALID)
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end
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end
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end
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end
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private
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def suppress_warnings
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original_verbosity = $VERBOSE
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$VERBOSE = nil
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yield
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$VERBOSE = original_verbosity
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end
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end
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