def METHOD_NAME() -> None:
    directions = [StudyDirection.MINIMIZE, StudyDirection.MAXIMIZE]
    # Check all pairs of trials consisting of these values, i.e.,
    # [-inf, -inf], [-inf, -1], [-inf, 1], [-inf, inf], [-1, -inf], ...
    # These values should be specified in ascending order.
    vals = [-float("inf"), -1, 1, float("inf")]
    # The following table illustrates an example of dominance relations.
    # "d" cells in the table dominates the "t" cell in (MINIMIZE, MAXIMIZE) setting.
    #
    #                        value1
    #        ╔═════╤═════╤═════╤═════╤═════╗
    #        ║     │ -∞  │ -1  │  1  │  ∞  ║
    #        ╟─────┼─────┼─────┼─────┼─────╢
    #        ║ -∞  │     │     │  d  │  d  ║
    #        ╟─────┼─────┼─────┼─────┼─────╢
    #        ║ -1  │     │     │  d  │  d  ║
    # value0 ╟─────┼─────┼─────┼─────┼─────╢
    #        ║  1  │     │     │  t  │  d  ║
    #        ╟─────┼─────┼─────┼─────┼─────╢
    #        ║  ∞  │     │     │     │     ║
    #        ╚═════╧═════╧═════╧═════╧═════╝
    #
    # In the following code, we check that for each position of "t" cell, the relation
    # above holds.
    # Generate the set of all possible indices.
    all_indices = set((i, j) for i in range(len(vals)) for j in range(len(vals)))
    for t_i, t_j in all_indices:
        # Generate the set of all indices that dominates the current index.
        dominating_indices = set(
            (d_i, d_j) for d_i in range(t_i + 1) for d_j in range(t_j, len(vals))
        )
        dominating_indices -= {(t_i, t_j)}
        for d_i, d_j in dominating_indices:
            trial1 = create_trial(values=[vals[t_i], vals[t_j]])
            trial2 = create_trial(values=[vals[d_i], vals[d_j]])
            assert _dominates(trial2, trial1, directions)
        for d_i, d_j in all_indices - dominating_indices:
            trial1 = create_trial(values=[vals[t_i], vals[t_j]])
            trial2 = create_trial(values=[vals[d_i], vals[d_j]])
            assert not _dominates(trial2, trial1, directions)