**Description**

For a DAG that looks like this:

```
A >> B
```

If A fails, B goes into "upstream_failed" state. If a user then marks A "success", B will remain in "upstream_failed" state. It will not automatically start running. This scenario often happens if the failure of A is dealt with outside of Airflow and the user does not want Airflow to run A again. But he usually expect Airflow to run B after A is marked "success".

**Use case / motivation**

After A is marked "success", its downstream tasks B should be cleared automatically and get ready to be scheduled. To avoid changing this behaviour completely, there can be a toggle button next to "Success" that lets the user decide if he wants Airflow to automatically clear downstream tasks that are in "upstream_failed" state.
airflow/models/dag.py
self,
        start_date: datetime,
        num: Optional[int] = None,
        end_date: Optional[datetime] = timezone.utcnow(),
    ) -> List[datetime]:
        if num is not None:
            end_date = None
        return utils_date_range(
            start_date=start_date, end_date=end_date, num=num, delta=self.normalized_schedule_interval
        )
    def is_fixed_time_schedule(self):
        """
        Figures out if the DAG schedule has a fixed time (e.g. 3 AM).
        :return: True if the schedule has a fixed time, False if not.
        """
        now = datetime.now()
        cron = croniter(self.normalized_schedule_interval, now)
        start = cron.get_next(datetime)
        cron_next = cron.get_next(datetime)
        if cron_next.minute == start.minute and cron_next.hour == start.hour:
            return True
        return False
    def following_schedule(self, dttm):