}
    synchronized void insert(String path, DfsReferral dr) {
        int s1, s2;
        String server, share, key;

        if (DISABLED)
            return;

        s1 = path.indexOf('\\', 1);
        s2 = path.indexOf('\\', s1 + 1);
        server = path.substring(1, s1);
        share = path.substring(s1 + 1, s2);

        key = path.substring(0, dr.pathConsumed).toLowerCase();

        return di - start;
    }
    public static String dec_utf8( byte[] src, int si, int slim ) throws IOException {
        char[] uni = new char[slim - si];
        int ui, ch;

        for( ui = 0; si < slim && (ch = src[si++] & 0xFF) != 0; ui++ ) {
            if( ch < 0x80 ) {
                uni[ui] = (char)ch;
            } else if((ch & 0xE0) == 0xC0 ) {
                if((slim - si) < 2 ) {
                    break;

/**
 */
@Named("default")
@Singleton
public class DefaultRepositoryLayout implements ArtifactRepositoryLayout {
    private static final char PATH_SEPARATOR = '/';

    private static final char GROUP_SEPARATOR = '.';

    private static final char ARTIFACT_SEPARATOR = '-';

    public String getId() {
        return "default";
    }

    public String pathOf(Artifact artifact) {

//
// The filled `device` struct and the allocated `device_info` struct may be
// passed to TFE_RegisterCustomDevice. The `device_name` arguments must match.
void AllocateParallelDevice(const char* device_name,
                            const char* const* underlying_devices,
                            int num_underlying_devices,
                            TFE_CustomDevice* device, void** device_info);

}  // namespace parallel_device

  TFE_ContextOptionsSetAsync(opts, static_cast<unsigned char>(async));
  TFE_Context* ctx = TFE_NewContext(opts, status.get());
  TFE_DeleteContextOptions(opts);
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TFE_TensorHandle* hcpu = TestMatrixTensorHandle(ctx);
  const char* kErrorDevice = "NoSuchDevice:0";
  TFE_TensorHandle* hdevice =

    // requests been enqueued.
    for (int i = 0; i < 50; ++i) {
      handles_task0.push_back(TestMatrixTensorHandle(ctx));
    }
  }
  const char task1_name[] = "/job:localhost/replica:0/task:1/device:CPU:0";
  const char task2_name[] = "/job:localhost/replica:0/task:2/device:CPU:0";

  std::vector<TFE_TensorHandle*> handles_task2;
  for (auto* h_task0 : handles_task0) {
    handles_task2.push_back(

            bufferSize = DEFAULT_BUF_SIZE;
        }
        char[] buf = new char[bufferSize];
        int size = 0;
        int len;
        try {
            while ((len = reader.read(buf, size, bufferSize - size)) != -1) {
                size += len;
                if (size == bufferSize) {
                    final char[] newBuf = new char[bufferSize + initialCapacity];

    public List<Character> create(Character[] elements) {
      char[] chars = Chars.toArray(asList(elements));
      return charactersOf(String.copyValueOf(chars));
    }
  }

  public static class CharactersOfCharSequenceGenerator extends TestCharacterListGenerator {
    @Override
    public List<Character> create(Character[] elements) {
      char[] chars = Chars.toArray(asList(elements));

The value returned by [sha1.New] now also implements the [encoding.BinaryAppender] interface....

@ElementTypesAreNonnullByDefault
public class TreeTraverserTest extends TestCase {
  private static class Node {
    final char value;

    Node(char value) {
      this.value = value;
    }
  }

  private static final class Tree extends Node {
    final List<Tree> children;

    public Tree(char value, Tree... children) {
      super(value);
      this.children = asList(children);
    }
  }