def METHOD_NAME(sample_without_replacement):
    # This test is heavily inspired from test_random.py of python-core.
    #
    # For the entire allowable range of 0 <= k <= N, validate that
    # sample generates all possible permutations
    n_population = 10
    # a large number of trials prevents false negatives without slowing normal
    # case
    n_trials = 10000
    for n_samples in range(n_population):
        # Counting the number of combinations is not as good as counting the
        # the number of permutations. However, it works with sampling algorithm
        # that does not provide a random permutation of the subset of integer.
        n_expected = comb(n_population, n_samples, exact=True)
        output = {}
        for i in range(n_trials):
            output[frozenset(sample_without_replacement(n_population, n_samples))] = (
                None
            )
            if len(output) == n_expected:
                break
        else:
            raise AssertionError(
                "number of combinations != number of expected (%s != %s)"
                % (len(output), n_expected)
            )