### Apache Airflow version

2.2.0b2 (beta snapshot)

### Operating System

ubuntu 20.04

### Versions of Apache Airflow Providers

n/a

### Deployment

Virtualenv installation

### Deployment details

pip install /path/to/airflow/src

### What happened

Given any DAG initialized with: `schedule_interval=None`

Run `airflow dags test mydagname $(date +%Y-%m-%d)` and get an error:

```
INFO - No run dates were found for the given dates and dag interval.
```

This behavior changed in https://github.com/apache/airflow/pull/15397, it used to trigger a backfill dagrun at the given date.

### What you expected to happen

I expected a backfill dagrun with the given date, regardless of whether it fit into the `schedule_interval`.

If AIP-39 made that an unrealistic expectation, then I'd hope for some way to define unscheduled dags which can still be tested from the command line (which, so far as I know, is the fastest way to iterate on a DAG.).

As it is, I keep changing `schedule_interval` back and forth depending on whether I want to iterate via `astro dev start` (which tolerates `None` but does superfluous work if the dag is scheduled) or via `airflow dags test ...` (which doesn't tolerate `None`).

### How to reproduce

Initialize a DAG with: `schedule_interval=None` and run it via `airflow dags test mydagname $(date +%Y-%m-%d)`

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/models/dag.py
self, start_date=None, end_date=None, state=None, session=None
    ) -> List[TaskInstance]:
        if not start_date:
            start_date = (timezone.utcnow() - timedelta(30)).date()
            start_date = timezone.make_aware(datetime.combine(start_date, datetime.min.time()))
        return (
            self._get_task_instances(
                task_ids=None,
                start_date=start_date,
                end_date=end_date,
                run_id=None,
                state=state,
                include_subdags=False,
                include_parentdag=False,
                include_dependent_dags=False,
                exclude_task_ids=[],
                as_pk_tuple=False,
                session=session,
            )
            .join(TaskInstance.dag_run)
            .order_by(DagRun.execution_date)
            .all()
        )
    @overload
    def _get_task_instances(