return normalizeWord(word);
  }

  private static String firstCharOnlyToUpper(String word) {
    return word.isEmpty()
        ? word
        : Ascii.toUpperCase(word.charAt(0)) + Ascii.toLowerCase(word.substring(1));
  }

    @Test
    @DisplayName("Test size calculation with short filename")
    void testSizeWithShortFilename() {
        FileRenameInformation2 info = new FileRenameInformation2("test.txt", false);
        // 20 bytes fixed + 2 * 8 chars = 20 + 16 = 36
        assertEquals(36, info.size());
    }

    @Test
    @DisplayName("Test size calculation with long filename")
    void testSizeWithLongFilename() {

  static final ImmutableMap<String, String> TEST_STRINGS =
      ImmutableMap.<String, String>builder()
          .put("empty", "")
          .put("1 char", "0")
          .put("1 word", "hello")
          .put("2 words", "hello world")
          .put("\\n line break", "hello\nworld")
          .put("\\r line break", "hello\rworld")

            if (targetUrl.indexOf('#') == -1) {
                final StringBuilder buf = new StringBuilder(value.length() + 100);
                for (final char c : value.toCharArray()) {
                    if (CharUtil.isUrlChar(c) || c == ' ') {
                        buf.append(c);
                    } else {
                        try {

											<la:message key="labels.login" />
										</la:link></li>
								</c:when>
							</c:choose>
							<c:if test="${chatEnabled}">
								<li class="nav-item"><la:link href="/chat"
										styleClass="nav-link" role="button" aria-haspopup="true"
										aria-expanded="false">
										<i class="fa fa-fw fa-robot" aria-hidden="true"></i>
										<la:message key="labels.chat_ai_mode" />

// and sets 'device_name' accordingly.
// `device_type` must be either "GPU" or "TPU".
bool GetDeviceName(TFE_Context* ctx, tensorflow::string* device_name,
                   const char* device_type);

// Create a ServerDef with the given `job_name` and add `num_tasks` tasks in it.
tensorflow::ServerDef GetServerDef(const tensorflow::string& job_name,
                                   int num_tasks);

 *
 * @author Adomas Paltanavicius
 */
@NullUnmarked
public class JoinerBenchmark {

  private static final String DELIMITER_STRING = ",";
  private static final char DELIMITER_CHARACTER = ',';

  private static final Joiner JOINER_ON_STRING = Joiner.on(DELIMITER_STRING);
  private static final Joiner JOINER_ON_CHARACTER = Joiner.on(DELIMITER_CHARACTER);

  @Param({"3", "30", "300"})

    Map<Class<?>, Class<?>> wrapToPrim = new LinkedHashMap<>(16);

    add(primToWrap, wrapToPrim, boolean.class, Boolean.class);
    add(primToWrap, wrapToPrim, byte.class, Byte.class);
    add(primToWrap, wrapToPrim, char.class, Character.class);
    add(primToWrap, wrapToPrim, double.class, Double.class);
    add(primToWrap, wrapToPrim, float.class, Float.class);
    add(primToWrap, wrapToPrim, int.class, Integer.class);

	switch t {
	case scanner.EOF:
		return "EOF"
	case scanner.Ident:
		return "identifier"
	case scanner.Int:
		return "integer constant"
	case scanner.Float:
		return "float constant"
	case scanner.Char:
		return "rune constant"
	case scanner.String:
		return "string constant"
	case scanner.RawString:
		return "raw string constant"
	case scanner.Comment:
		return "comment"
	default:

      Headers
        .Builder()
        .addUnsafeNonAscii("héader1", "value1")
        .build()
    }.also { expected ->
      assertThat(expected.message).isEqualTo("Unexpected char 0xe9 at 1 in header name: héader1")
    }
  }

  @Test fun addUnsafeNonAsciiAcceptsUnicodeValue() {
    val headers =
      Headers
        .Builder()
        .addUnsafeNonAscii("header1", "valué1")