// This is usually orders of magnitude faster than actually sorting.
func (m metaCacheEntries) isSorted() bool {
	return sort.SliceIsSorted(m, m.less)
}

// shallowClone will create a shallow clone of the array objects,
// but object metadata will not be cloned.
func (m metaCacheEntries) shallowClone() metaCacheEntries {
	dst := make(metaCacheEntries, len(m))
	copy(dst, m)
	return dst
}

            // Mock that it exists and is a directory
            doReturn(true).when(smbFile).exists();
            doReturn(true).when(smbFile).isDirectory();

            // Mock listFiles to return empty array (directory is empty)
            doReturn(new SmbFile[0]).when(smbFile).listFiles();

            when(mockTreeHandle.isSMB2()).thenReturn(false);

import static com.google.common.collect.testing.features.ListFeature.SUPPORTS_SET;
import static com.google.common.collect.testing.testers.ReflectionFreeAssertThrows.assertThrows;
import static java.util.Arrays.asList;
import static java.util.Collections.emptyList;
import static java.util.Collections.singletonList;

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;

Por padrão, tudo **"simplesmente funciona"**.

### Validação

* Validação para a maioria dos (ou todos?) **tipos de dados** do Python, incluindo:
    * objetos JSON (`dict`).
    * arrays JSON (`list`), definindo tipos dos itens.
    * campos String (`str`), definindo tamanho mínimo e máximo.
    * Numbers (`int`, `float`) com valores mínimos e máximos, etc.

* Validação de tipos mais exóticos, como:

        recordNameField.setAccessible(true);
        Name mockRecordName = new Name(mockConfig);
        recordNameField.set(nameQueryResponse, mockRecordName);

        // Prepare a byte array with valid NetBIOS name format
        byte[] src = new byte[100];
        int srcIndex = 0;

        // Start with compressed name pointer (0xC0) to use questionName
        src[srcIndex] = (byte) 0xC0;

        // valueOf should return the same instance
        CrawlerStatus status3 = CrawlerStatus.valueOf("INITIALIZING");
        assertSame(status1, status3);
        assertTrue(status1 == status3);

        // values() array contains the same instances
        CrawlerStatus status4 = CrawlerStatus.values()[0];
        assertSame(status1, status4);
        assertTrue(status1 == status4);
    }

    /**
     * Test enum as map key

package org.codelibs.fess.sso.aad;

import static org.codelibs.core.stream.StreamUtil.split;

import java.io.IOException;
import java.net.URI;
import java.net.URLEncoder;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Locale;
import java.util.Map;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;

    @Mock
    private HttpServletRequest mockRequest;

    @Mock
    private HttpServletResponse mockResponse;

    private NtlmSsp ntlmSsp;

    // A sample challenge array
    private final byte[] challenge = new byte[] { 0x01, 0x23, 0x45, 0x67, (byte) 0x89, (byte) 0xab, (byte) 0xcd, (byte) 0xef };

    // Base64 encoded Type 1 message: NTLMSSP, Type 1, flags=0x00088207

Pero por defecto, todo **"simplemente funciona"**.

### Validación

* Validación para la mayoría (¿o todas?) de los **tipos de datos** de Python, incluyendo:
    * Objetos JSON (`dict`).
    * Array JSON (`list`) definiendo tipos de elementos.
    * Campos de cadena de caracteres (`str`), definiendo longitudes mínimas y máximas.
    * Números (`int`, `float`) con valores mínimos y máximos, etc.

        assertFalse(ctx.isPreferredMech(null));
        assertFalse(ctx.isSupported(new ASN1ObjectIdentifier("1.3.6.1.4.1.99999")));
    }

    @Test
    @DisplayName("getSupportedMechs returns expected array")
    void getSupportedMechs_happyPath() {
        ASN1ObjectIdentifier[] mechs = ctx.getSupportedMechs();
        assertNotNull(mechs);
        assertArrayEquals(Kerb5Context.SUPPORTED_MECHS, mechs);
    }