* KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.profiles.activation;

/**
 * ProfileActivationException
 */
@Deprecated
public class ProfileActivationException extends Exception {

    private static final long serialVersionUID = -90820222109103638L;

            RenderDataUtil.register(data, "notification", fessConfig.getNotificationLogin());
            saveToken();
        });
    }

    /**
     * Handles user login with the provided credentials.
     *
     * @param form the login form containing username and password
     * @return the HTML response after login attempt
     */
    @Execute
    public HtmlResponse login(final LoginForm form) {

  public static <T> T reserialize(T object) {
    return Platform.reserialize(object);
  }

  /**
   * Serializes and deserializes the specified object and verifies that the re-serialized object is
   * equal to the provided object, that the hashcodes are identical, and that the class of the
   * re-serialized object is identical to that of the original.
   *
   * <p><b>GWT warning:</b> Under GWT, this method simply returns its input, as proper GWT

 * change the behavior of {@link #equals}, which can lead to unexpected behavior. In this case, you
 * should override {@code equals} as well, either providing your own implementation, or delegating
 * to the provided {@code standardEquals} method.
 *
 * <p>Each of the {@code standard} methods, where appropriate, use {@link Objects#equals} to test
 * equality for both keys and values. This may not be the desired behavior for map implementations

 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *
 * <p>Note that this implementation is not synchronized. If multiple threads access this table

 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *
 * <p>Note that this implementation is not synchronized. If multiple threads access this table

 * the behaviour of {@link #offer} which can lead to unexpected behaviour. In this case, you should
 * override {@code offer} as well, either providing your own implementation, or delegating to the
 * provided {@code standardOffer} method.
 *
 * <p><b>{@code default} method warning:</b> This class does <i>not</i> forward calls to {@code
 * default} methods. Instead, it inherits their default implementations. When those implementations

import org.junit.jupiter.api.Assumptions.assumeTrue
import org.junit.jupiter.api.BeforeEach
import org.junit.jupiter.api.extension.RegisterExtension
import org.junit.jupiter.params.ParameterizedTest
import org.junit.jupiter.params.provider.ValueSource

class SessionReuseTest {
  @JvmField @RegisterExtension
  var platform = PlatformRule()

  @JvmField @RegisterExtension
  val clientTestRule = OkHttpClientTestRule()

        assertDoesNotThrow(() -> dfsImpl.cache(mockContext, "\\\\server\\share\\path", mockReferral));
    }

    @Test
    void testCache_InvalidPath() {
        // Scenario: The UNC path provided is invalid.
        DfsReferralDataInternal mockReferral = mock(DfsReferralDataInternal.class);
        // Should not throw any exception.
        assertDoesNotThrow(() -> dfsImpl.cache(mockContext, "invalidpath", mockReferral));

# Automatic Site Replication

This feature allows multiple independent MinIO sites (or clusters) that are using the same external IDentity Provider (IDP) to be configured as replicas. In this situation the set of replica sites are referred to as peer sites or just sites. When site-replication is enabled on a set of sites, the following changes are replicated to all other sites:

- Creation and deletion of buckets and objects