**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 not task_instance:
                return None
            
            
            
            task_instance_data = [
                task_instance.state,
                task_instance.try_number,
                None,  
                None,  
            ]
            if task_instance.start_date:
                
                task_instance_data[2] = int(task_instance.start_date.timestamp())
                if task_instance.duration is not None:
                    task_instance_data[3] = truncate_task_duration(task_instance.duration)
            return task_instance_data
        def recurse_nodes(task, visited):