import java.util.concurrent.atomic.AtomicInteger;
import junit.framework.TestCase;

/**
 * Basher test for {@link ConcurrentHashMultiset}: start a bunch of threads, have each of them do
 * operations at random. Each thread keeps track of the per-key deltas that it's directly
 * responsible for; after all threads have completed, we sum the per-key deltas and compare to the
 * existing multiset values.
 *
 * @author mike nonemacher
 */

        return CacheUtils.pluginEquals(a, b);
    }

    public void register(MavenProject project, Key cacheKey, CacheRecord record) {
        // default cache does not track record usage
    }

        return CacheUtils.pluginEquals(a, b);
    }

    public void register(MavenProject project, Key key, CacheRecord record) {
        // default cache does not track plugin usage
    }

    public void dispose() {
        flush();
    }

Running the controller actually starts processing things.
Normally, this just means running the queue.
All informers created by `kube.Client` are kept track in the client, and started in one go with `RunAndWait` in one centralized call.
As a result, each individual controllers should simply wait until informers have synced, then run the queue to start processing things.

In diesen Fällen können Sie die Python-Technik zum „Entpacken“ eines `dict`s mit `**dict_to_unpack` verwenden:

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

For those cases, you can use the Python technique of "unpacking" a `dict` with `**dict_to_unpack`:

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

### EventListener.Factory

      ReferenceQueue<Object> queue,
      PhantomReference<Object> frqReference) {
    this.queue = queue;

    this.finalizableReferenceClassReference = new WeakReference<>(finalizableReferenceClass);

    // Keep track of the FRQ that started us so we know when to stop.
    this.frqReference = frqReference;
  }

  /** Loops continuously, pulling references off the queue and cleaning them up. */

      int n, @Nullable Entry<K, V>[] entryArray, boolean throwIfDuplicateKeys) {
    Map<K, V> delegateMap = Maps.newHashMapWithExpectedSize(n);
    // If duplicates are allowed, this map will track the last value for each duplicated key.
    // A second pass will retain only the first entry for that key, but with this last value. The
    // value will then be replaced by null, signaling that later entries with the same key should

Dans ces cas, vous pouvez utiliser la technique Python "d'affection par décomposition" (appelé _unpacking_ en anglais) d'un `dict` avec `**dict_to_unpack` :

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```