}
          };
      executor.execute(errorTask);
      service.execute(barrierTask); // submit directly to the service
      // the barrier task runs after the error task so we know that the error has been observed by
      // SequentialExecutor by the time the barrier is satisfied
      barrier.await(1, SECONDS);
      executor.execute(barrierTask);
      // timeout means the second task wasn't even tried

        // Assert
        assertSame(session, result);
        verify(handle).getSession();
    }

    @Test
    @DisplayName("getSession(): may return null and should be observed as such")
    void getSession_returnsNull() {
        // Arrange
        when(handle.getSession()).thenReturn(null);

        // Act
        SmbSession result = handle.getSession();

        // Assert

     *
     * @see jcifs.util.transport.Response#verifySignature(byte[], int, int)
     */
    @Override
    public boolean verifySignature(final byte[] buffer, final int i, final int size) {
        // observed too that signatures on error responses are sometimes wrong??
        // Looks like the failure case also is just reflecting back the signature we sent

    server.requireClientAuth()
    val call = client.newCall(Request.Builder().url(server.url("/")).build())
    assertFailsWith<IOException> {
      call.execute()
    }

    // Observed Events are variable
    // JDK 14
    // CallStart, ProxySelectStart, ProxySelectEnd, DnsStart, DnsEnd, ConnectStart, SecureConnectStart,

   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to
   * accommodate as many threads as will ever concurrently modify the table. Using a significantly

      }
    }
    int oldValue = existingCounter.get();
    if (oldValue == expectedOldCount) {
      if (oldValue == 0) {
        if (newCount == 0) {
          // Just observed a 0; try to remove the entry to clean up the map
          countMap.remove(element, existingCounter);
          return true;
        } else {
          AtomicInteger newCounter = new AtomicInteger(newCount);

      }

      return value;
    }

    /**
     * Performs routine cleanup following a read. Normally cleanup happens during writes, or from
     * the cleanupExecutor. If cleanup is not observed after a sufficient number of reads, try
     * cleaning up from the read thread.
     */
    void postReadCleanup() {
      if ((readCount.incrementAndGet() & DRAIN_THRESHOLD) == 0) {
        runCleanup();

can be tested. This section summarizes what one needs to take into consideration so that
tests won't fail when run in fips mode.

=== Muting tests in FIPS 140-2 mode

If the following limitations cannot be observed, or there is a need to actually test some use
case that is not available/allowed in fips mode, the test can be muted. For unit tests or Java
rest tests one can use

------------------------------------------------

 *   <dt>An IPv6 "IPv4 mapped" address, {@code "::ffff:192.168.0.1"}.
 *   <dd>{@code 00 00 00 00 00 00 00 00 00 00 ff ff c0 a8 00 01}
 * </dl>
 *
 * <p>A few notes about IPv6 "IPv4 mapped" addresses and their observed use in Java.
 *
 * <p>"IPv4 mapped" addresses were originally a representation of IPv4 addresses for use on an IPv6
 * socket that could receive both IPv4 and IPv6 connections (by disabling the {@code IPV6_V6ONLY}

   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to
   * accommodate as many threads as will ever concurrently modify the table. Using a significantly