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