}

  protected final E e0() {
    return samples.e0();
  }

  protected final E e1() {
    return samples.e1();
  }

  protected final E e2() {
    return samples.e2();
  }

  protected final E e3() {
    return samples.e3();
  }

  protected final E e4() {
    return samples.e4();
  }

- how to categorize the problems so that the id of the problem can be match to a page with descriptive help and the test
  project
- nice little sample projects that could be run in the core as well as integration tests

All Possible Errors
- invalid lifecycle phase (maybe same as bad CLI param, though you were talking about embedder too)
- <module> specified is not found
- malformed settings
- malformed POM

- MinIO exports Prometheus compatible data by default which is resource centric as an authorized endpoint at `/minio/v2/metrics/resource`.

All of these can be accessed via Prometheus dashboard. A sample list of exposed metrics along with their definition is available on our public demo server at

```sh
curl https://play.min.io/minio/v2/metrics/cluster
```

### List of metrics reported Cluster and Bucket level

        // Verify a sample of encrypted messages can be decrypted (to avoid extensive decryption that might fail)
        int sampleSize = Math.min(5, encrypted.size());
        for (int i = 0; i < sampleSize; i++) {
            try {
                byte[] decrypted = context.decryptMessage(encrypted.get(i));
                assertArrayEquals(messages.get(i).getBytes(), decrypted, "Sample message " + i + " should decrypt correctly");

then GCD algorithm provides affinity towards odd number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity is given towards nodes which leads to next best GCD factor of 12 which provides uniform distribution.

- In...

 * is desired.
 *
 * <table border="1">
 * <caption>SmbNamedPipe Constructor Examples</caption>
 * <tr>
 * <td colspan="2"><b><code>SmbNamedPipe</code> Constructor Examples</b></td>
 * <tr><td ><b>Code Sample</b></td><td><b>Description</b></td></tr>
 * <tr><td ><pre>
 * new SmbNamedPipe( "smb1://server/IPC$/PIPE/foo",
 *         SmbNamedPipe.PIPE_TYPE_RDWR |
 *         SmbNamedPipe.PIPE_TYPE_CALL );
 * </pre></td><td>

    checkState(count() != 0);
    return sumOfProductsOfDeltas / count();
  }

  /**
   * Returns the sample covariance of the values. The count must be greater than one.
   *
   * <p>This is not guaranteed to return zero when the dataset consists of the same pair of values
   * multiple times, due to numerical errors.
   *
   * <h3>Non-finite values</h3>
   *

        // Setup: No "Authorization" header to follow a simple path
        when(mockRequest.getHeader("Authorization")).thenReturn(null);

        // Execute
        NtlmPasswordAuthentication result = ntlmSsp.doAuthentication(mockCifsContext, mockRequest, mockResponse, challenge);

        // Verify that the behavior is the same as calling the static method directly

    address[b++] = (value.ushr(8) and 0xff).toByte()
    address[b++] = (value and 0xff).toByte()
  }

  // All done. If compression happened, we need to move bytes to the right place in the
  // address. Here's a sample:
  //
  //      input: "1111:2222:3333::7777:8888"
  //     before: { 11, 11, 22, 22, 33, 33, 00, 00, 77, 77, 88, 88, 00, 00, 00, 00  }
  //   compress: 6
  //          b: 10

    checkState(count() != 0);
    return sumOfProductsOfDeltas / count();
  }

  /**
   * Returns the sample covariance of the values. The count must be greater than one.
   *
   * <p>This is not guaranteed to return zero when the dataset consists of the same pair of values
   * multiple times, due to numerical errors.
   *
   * <h3>Non-finite values</h3>
   *