**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/www/views.py
commit=True,
            )
            flash(f"Marked {state} on {len(altered)} task instances")
            return redirect(origin)
        to_be_altered = set_state(
            tasks=[task],
            execution_date=execution_date,
            upstream=upstream,
            downstream=downstream,
            future=future,
            past=past,
            state=state,
            commit=False,
        )
        details = "\n".join(str(t) for t in to_be_altered)
        response = self.render_template(
            "airflow/confirm.html",
            message=f"Here's the list of task instances you are about to mark as {state}:",
            details=details,
        )
        return response
    @expose('/failed', methods=['POST'])
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_EDIT, permissions.RESOURCE_TASK_INSTANCE),
        ]
    )
    @action_logging
    def failed(self):