**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
"""View to show dependencies between DAGs"""
    refresh_interval = timedelta(
        seconds=conf.getint(
            "webserver",
            "dag_dependencies_refresh_interval",
            fallback=conf.getint("scheduler", "dag_dir_list_interval"),
        )
    )
    last_refresh = timezone.utcnow() - refresh_interval
    nodes = []
    edges = []
    @expose('/dag-dependencies')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG_DEPENDENCIES),
        ]
    )
    @gzipped
    @action_logging
    def list(self):