**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
dep_context = DepContext(SCHEDULER_QUEUED_DEPS)
        failed_dep_reasons = [
            (dep.dep_name, dep.reason) for dep in ti.get_failed_dep_statuses(dep_context=dep_context)
        ]
        title = "Task Instance Details"
        return self.render_template(
            'airflow/task.html',
            task_attrs=task_attrs,
            ti_attrs=ti_attrs,
            failed_dep_reasons=failed_dep_reasons or no_failed_deps_result,
            task_id=task_id,
            execution_date=execution_date,
            special_attrs_rendered=special_attrs_rendered,
            form=form,
            root=root,
            dag=dag,
            title=title,
        )
    @expose('/xcom')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_XCOM),
        ]
    )
    @action_logging
    @provide_session
    def xcom(self, session=None):