**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
"""
        Simple utility method to set dependency between two tasks that
        already have been added to the DAG using add_task()
        """
        self.get_task(upstream_task_id).set_downstream(self.get_task(downstream_task_id))
    @provide_session
    def get_task_instances(self, start_date=None, end_date=None, state=None, session=None):