MinMaxPriorityQueue<Integer> q = MinMaxPriorityQueue.create(perm);
        q.removeAt(i);
        assertIntactUsingStartedWith(perm, q);
      }
    }
  }

  /** Regression test for bug found. */
  public void testCorrectOrdering_regression() {
    MinMaxPriorityQueue<Integer> q = MinMaxPriorityQueue.create(ImmutableList.of(3, 5, 1, 4, 7));
    List<Integer> expected = ImmutableList.of(1, 3, 4, 5, 7);

import java.util.concurrent.locks.LockSupport;
import junit.framework.TestCase;
import org.checkerframework.checker.nullness.qual.Nullable;

public final class InterruptibleTaskTest extends TestCase {

  // Regression test for a deadlock where a task could be stuck busy waiting for the task to
  // transition to DONE
  public void testInterruptThrows() throws Exception {
    final CountDownLatch isInterruptibleRegistered = new CountDownLatch(1);

  }

  /**
   * Returns a linear transformation giving the best fit to the data according to <a
   * href="http://mathworld.wolfram.com/LeastSquaresFitting.html">Ordinary Least Squares linear
   * regression</a> of {@code y} as a function of {@code x}. The count must be greater than one, and
   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code

import java.util.concurrent.locks.LockSupport;
import junit.framework.TestCase;
import org.checkerframework.checker.nullness.qual.Nullable;

public final class InterruptibleTaskTest extends TestCase {

  // Regression test for a deadlock where a task could be stuck busy waiting for the task to
  // transition to DONE
  public void testInterruptThrows() throws Exception {
    final CountDownLatch isInterruptibleRegistered = new CountDownLatch(1);

    @GwtIncompatible // decodingStream(Reader)
    DECODING_STREAM {
      @Override
      void assertFailsToDecode(
          BaseEncoding encoding, String cannotDecode, @Nullable String expectedMessage) {
        // Regression test for case where DecodingException was swallowed by default implementation
        // of
        // InputStream.read(byte[], int, int)
        // See https://github.com/google/guava/issues/3542

            return orig;
          }
        });
    assertThat(orig.toString())
        .contains("Exception thrown from implementation: class java.lang.StackOverflowError");
  }

  // Regression test for a case where we would fail to execute listeners immediately on done futures
  // this would be observable from an afterDone callback
  public void testListenersExecuteImmediately_fromAfterDone() {

    @GwtIncompatible // decodingStream(Reader)
    DECODING_STREAM {
      @Override
      void assertFailsToDecode(
          BaseEncoding encoding, String cannotDecode, @Nullable String expectedMessage) {
        // Regression test for case where DecodingException was swallowed by default implementation
        // of
        // InputStream.read(byte[], int, int)
        // See https://github.com/google/guava/issues/3542

        MinMaxPriorityQueue<Integer> q = MinMaxPriorityQueue.create(perm);
        q.removeAt(i);
        assertIntactUsingStartedWith(perm, q);
      }
    }
  }

  /** Regression test for bug found. */
  public void testCorrectOrdering_regression() {
    MinMaxPriorityQueue<Integer> q = MinMaxPriorityQueue.create(ImmutableList.of(3, 5, 1, 4, 7));
    List<Integer> expected = ImmutableList.of(1, 3, 4, 5, 7);

            return orig;
          }
        });
    assertThat(orig.toString())
        .contains("Exception thrown from implementation: class java.lang.StackOverflowError");
  }

  // Regression test for a case where we would fail to execute listeners immediately on done futures
  // this would be observable from an afterDone callback
  public void testListenersExecuteImmediately_fromAfterDone() {

  }

  /**
   * Returns a linear transformation giving the best fit to the data according to <a
   * href="http://mathworld.wolfram.com/LeastSquaresFitting.html">Ordinary Least Squares linear
   * regression</a> of {@code y} as a function of {@code x}. The count must be greater than one, and
   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code