**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
"""
        Get the Default DAG View, returns the default config value if DagModel does not
        have a value
        """
        
        return self.default_view or conf.get('webserver', 'dag_default_view').lower()
    @property
    def safe_dag_id(self):
        return self.dag_id.replace('.', '__dot__')
    @provide_session
    def set_is_paused(self, is_paused: bool, including_subdags: bool = True, session=None) -> None:
        """
        Pause/Un-pause a DAG.
        :param is_paused: Is the DAG paused
        :param including_subdags: whether to include the DAG's subdags
        :param session: session
        """
        filter_query = [
            DagModel.dag_id == self.dag_id,
        ]
        if including_subdags:
            filter_query.append(DagModel.root_dag_id == self.dag_id)
        session.query(DagModel).filter(or_(*filter_query)).update(
            {DagModel.is_paused: is_paused}, synchronize_session='fetch'
        )
        session.commit()
    @classmethod
    @provide_session
    def deactivate_deleted_dags(cls, alive_dag_filelocs: List[str], session=None):