} catch (Exception e) { // sneaky checked exception
            log.get().log(Level.SEVERE, "Exception while executing runnable " + task, e);
          } finally {
            task = null;
          }
        }
      } finally {
        // Ensure that if the thread was interrupted at all while processing the task queue, it
        // is returned to the delegate Executor interrupted so that it may handle the

 *
 * Typical use loops over the parts in sequence:
 *
 * ```kotlin
 * val response: Response = call.execute()
 * val multipartReader = MultipartReader(response.body!!)
 *
 * multipartReader.use {
 *   while (true) {
 *     val part = multipartReader.nextPart() ?: break
 *     process(part.headers, part.body)
 *   }
 * }
 * ```
 *

        int i = 0, n = -5;

        if (off + len > b.length) {
            throw new IOException("Buffer too short, bufsize " + b.length + " read " + len);
        }

        while (i < len) {
            n = in.read(b, off + i, len - i);
            if (n <= 0) {
                break;
            }
            i += n;
        }

        return i;
    }

    /*

import java.util.Iterator;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * A map-like data structure that wraps a backing map and caches values while iterating through
 * {@link #unmodifiableKeySet()}. By design, the cache is cleared when this structure is mutated. If
 * this structure is never mutated, it provides a thread-safe view of the backing map.
 *

                int len = 0;
                // Use appropriate string decoding based on Unicode flag
                try {
                    if ((flags2 & FLAGS2_UNICODE) == FLAGS2_UNICODE) {
                        while (buffer[bufferIndex + len] != (byte) 0x00 || buffer[bufferIndex + len + 1] != (byte) 0x00) {
                            len += 2;
                            if (len > 256) {

    return stream.readInt();
  }

  /**
   * Stores the contents of a map in an output stream, as part of serialization. It does not support
   * concurrent maps whose content may change while the method is running.
   *
   * <p>The serialized output consists of the number of entries, first key, first value, second key,
   * second value, and so on.
   */

      var i = 0
      val length = logMessage.length
      while (i < length) {
        var newline = logMessage.indexOf('\n', i)
        newline = if (newline != -1) newline else length
        do {
          val end = minOf(newline, i + MAX_LOG_LENGTH)
          Log.println(logLevel, tag, logMessage.substring(i, end))
          i = end
        } while (i < newline)
        i++
      }
    }
  }

   */
  static BigInteger randomPositiveBigInteger(int numBits) {
    BigInteger result;
    do {
      result = randomNonNegativeBigInteger(numBits);
    } while (result.signum() == 0);
    return result;
  }

  /**
   * Generates a number in [0, 2^numBits) with an exponential distribution. The floor of the log2 of

    if (byteCount == 0L) {
      writer.data(outFinished, streamId, buffer, 0)
      return
    }

    var byteCount = byteCount
    while (byteCount > 0L) {
      var toWrite: Int
      withLock {
        try {
          while (writeBytesTotal >= writeBytesMaximum) {
            // Before blocking, confirm that the stream we're writing is still open. It's possible

  @CanIgnoreReturnValue
  private Map<R, V> removeColumn(@Nullable Object column) {
    Map<R, V> output = new LinkedHashMap<>();
    Iterator<Entry<R, Map<C, V>>> iterator = backingMap.entrySet().iterator();
    while (iterator.hasNext()) {
      Entry<R, Map<C, V>> entry = iterator.next();
      V value = entry.getValue().remove(column);
      if (value != null) {
        output.put(entry.getKey(), value);