**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
if task.depends_on_past:
                node['depends_on_past'] = task.depends_on_past
            if task.start_date:
                
                node['start_ts'] = int(task.start_date.timestamp())
                if task.end_date:
                    
                    node['end_ts'] = int(task.end_date.timestamp())
            if task.extra_links:
                node['extra_links'] = task.extra_links
            return node
        return {
            'name': '[DAG]',
            'children': [recurse_nodes(t, set()) for t in dag.roots],
            'instances': [dag_runs.get(d) or {'execution_date': d.isoformat()} for d in dates],
        }
    @expose('/tree')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_LOG),
        ]
    )
    @gzipped  
    @action_logging  
    def tree(self):
        """Get Dag as tree."""
        dag_id = request.args.get('dag_id')
        dag = current_app.dag_bag.get_dag(dag_id)