} else {
                ""
            }
        description =
            "Builds Gradle with the version of Gradle which is currently under development (twice)$descriptionSuffix"

        requirements {
            requiresNotSharedHost()
        }

    /*
     To avoid unnecessary rerun, what we do here is a bit complicated:

        if (!advance()) {
          return endOfData();
        }
      }
    }
  }

  /**
   * If the graph is undirected, each unordered [node, otherNode] pair (except self-loops) will be
   * visited twice if there is an edge connecting them. To avoid returning duplicate {@link
   * EndpointPair}s, we keep track of the nodes that we have visited. When processing endpoint

			Owner:     "owner",
			Quorum:    &quorum,
		}
		ok, err := l.RLock(ctx, arg)
		if err != nil {
			t.Fatal(err)
		}
		if !ok {
			t.Fatal("did not get read lock")
		}
		// RLock twice
		ok, err = l.RLock(ctx, arg)
		if err != nil {
			t.Fatal(err)
		}
		if !ok {
			t.Fatal("did not get write lock")
		}

		rResources[i] = arg.Resources[0]
	}

                        } else {
                            return -1;
                        }
                    });
                    // Remove duplicates (equal adjacent elements) - a new, un@Incubating type will be here twice, as 2 errors are reported; use stringified JSON to compare
                    // Filtering an array is NOT in place

 *   <dt>{@link SetMultimap}
 *   <dd>An extension of {@link Multimap} which has order-independent equality and does not allow
 *       duplicate entries; that is, while a key may appear twice in a {@code SetMultimap}, each
 *       must map to a different value. {@code SetMultimap} takes its name from the fact that the
 *       {@linkplain SetMultimap#get collection of values} associated with a given key fulfills the

        //
        // Without de-duplication, the final list would contain E three times, once for E being in the projects and
        // whitelisted, and twice more for E being a downstream dependency of B and D.
        return filtered.stream().distinct().toList();
    }

    @Override
    public String toString() {
        return getSortedProjects().toString();
    }

        // Act: call methods, some multiple times
        String name = mockEntry.getName();
        int type1 = mockEntry.getType();
        int type2 = mockEntry.getType(); // called twice for interaction verification
        int attributes = mockEntry.getAttributes();
        long createTime = mockEntry.createTime();
        long lastModified = mockEntry.lastModified();

        // Act
        assertTrue(itr.hasNext());
        SmbResource r = itr.next();

        // Assert: filter was invoked twice and we got the accepted one
        ArgumentCaptor<SmbResource> captor = ArgumentCaptor.forClass(SmbResource.class);
        verify(filter, times(2)).accept(captor.capture());
        assertNotNull(r);

        JobNotFoundException exception = new JobNotFoundException(message);

        assertEquals(message, exception.getMessage());
        assertEquals(message, exception.getMessage()); // Call twice to verify consistency
        assertEquals(message, exception.getLocalizedMessage());
    }

    @Test
    public void test_toString() {
        // Test toString method

on 16 drive MinIO deployment. If you use eight data and eight parity drives, the file space usage will be approximately twice, i.e. 100 MiB
file will take 200 MiB space. But, if you use ten data and six parity drives, same 100 MiB file takes around 160 MiB. If you use 14 data and
two parity drives, 100 MiB file takes only approximately 114 MiB.