TensorFlow models, please demonstrate an exploit against one of Alphabet's
    models in <https://tfhub.dev/>
  - An explanation of who can exploit this vulnerability, and what they gain
    when doing so. Write an attack scenario that demonstrates how your issue
    violates the use cases and security assumptions defined in the threat model.
    This will help us evaluate your report quickly, especially if the issue is

This could be especially useful during testing, as it's very easy to override a dependency with your own custom settings.

### The config file

Coming from the previous example, your `config.py` file could look like:

```Python hl_lines="10"
{!../../docs_src/settings/app02/config.py!}
```

    final AtomicDouble at = new AtomicDouble(1.0);
    Thread t =
        newStartedThread(
            new CheckedRunnable() {
              @Override
              @SuppressWarnings("ThreadPriorityCheck") // doing our best to test for races
              public void realRun() {
                while (!at.compareAndSet(2.0, 3.0)) {
                  Thread.yield();
                }
              }
            });

  }

  /*
   * TODO(cpovirk): It would be great to run all these tests (including class unloading) in an
   * environment that forces Futures.getChecked to its fallback WeakSetValidator. One awful way of
   * doing so would be to derive a separate test library by using remove_from_jar to strip out
   * ClassValueValidator.
   *
   * Fortunately, we get pretty good coverage "by accident": We run all these tests against the

   * resizing the table, as well as populating slots with new Cells.
   * There is no need for a blocking lock; when the lock is not
   * available, threads try other slots (or the base).  During these
   * retries, there is increased contention and reduced locality,
   * which is still better than alternatives.
   *
   * Per-thread hash codes are initialized to random values.

require distributed deploying MinIO with Erasure Coding. For extended development and production, deploy MinIO with Erasure Coding enabled - specifically,
with a *minimum* of 4 drives per MinIO server. See [MinIO Erasure Code Overview](https://min.io/docs/minio/linux/operations/concepts/erasure-coding.html)
for more complete documentation.

### Stable

   * is now at some position before {@code index}. The second element is the one that was swapped
   * down to replace the element at {@code index}. This fact is used by iterator.remove so as to
   * visit elements during a traversal once and only once.
   */
  @VisibleForTesting
  @CanIgnoreReturnValue
  @CheckForNull
  MoveDesc<E> removeAt(int index) {
    checkPositionIndex(index, size);
    modCount++;
    size--;

            // If this CAS succeeds, we know that the provided callable will never be invoked,
            // so when oldFuture completes it is safe to allow the next submitted task to
            // proceed. Doing this immediately here lets the next task run without waiting for
            // the cancelled task's executor to run the noop AsyncCallable.
            //
            // ---
            //

		var hint string
		if endpoint.URL != nil {
			hint = fmt.Sprintf("Drive '%s' does not support O_DIRECT flags, MinIO erasure coding requires filesystems with O_DIRECT support", endpoint.Path)
		} else {
			hint = "Drives do not support O_DIRECT flags, MinIO erasure coding requires filesystems with O_DIRECT support"
		}
		logger.Fatal(config.ErrUnsupportedBackend(err).Hint("%s", hint), "Unable to initialize backend")

version `RELEASE.2021-09-02T09-21-27Z` or older supports only a single remote target per bucket. To take advantage of multiple destination replication, use the latest version of `mc`

Status of delete marker replication can be viewed by doing a GET/HEAD on the object version - it will return a `X-Minio-Replication-DeleteMarker-Status` header and http response code of `405`. In the case of permanent deletes, if the delete replication is pending or failed to propagate to the target cluster,...