**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
"""
        Set ``is_active=False`` on the DAGs for which the DAG files have been removed.
        Additionally change ``is_active=False`` to ``True`` if the DAG file exists.
        :param alive_dag_filelocs: file paths of alive DAGs
        :param session: ORM Session
        """
        log.debug("Deactivating DAGs (for which DAG files are deleted) from %s table ", cls.__tablename__)
        dag_models = session.query(cls).all()
        try:
            for dag_model in dag_models:
                if dag_model.fileloc is not None:
                    if correct_maybe_zipped(dag_model.fileloc) not in alive_dag_filelocs:
                        dag_model.is_active = False
                    else:
                        
                        
                        if not dag_model.is_active:
                            dag_model.is_active = True
                else:
                    continue
            session.commit()
        except Exception:
            session.rollback()
            raise
    @classmethod
    def dags_needing_dagruns(cls, session: Session):