this.totalCount = elemCount + totalCount(left) + totalCount(right);
    }

    private void recomputeHeight() {
      this.height = 1 + max(height(left), height(right));
    }

    private void recompute() {
      recomputeMultiset();
      recomputeHeight();
    }

    private AvlNode<E> rebalance() {
      switch (balanceFactor()) {
        case -2:

    reallyTestNoMatchThenMatch(matcher.precomputed().negate(), s);
  }

  private void doTestNoMatchThenMatch(CharMatcher matcher, String s) {
    reallyTestNoMatchThenMatch(matcher, s);
    reallyTestMatchThenNoMatch(matcher.negate(), s);
    reallyTestNoMatchThenMatch(matcher.precomputed(), s);
    reallyTestMatchThenNoMatch(matcher.negate().precomputed(), s);

    // b/80241237

    Cache<String, String> c = CacheBuilder.newBuilder().maximumSize(1).build();

    assertThat(c.asMap().compute("hash-1", (k, v) -> "a")).isEqualTo("a");
    assertThat(c.asMap().compute("hash-1", (k, v) -> "b")).isEqualTo("b");
    assertThat(c.asMap().compute("hash-1", (k, v) -> "c")).isEqualTo("c");
    assertThat(c.size()).isEqualTo(1);
    assertThat(c.asMap().computeIfAbsent("hash-2", k -> "")).isEqualTo("");

 *
 * <h3>Examples</h3>
 *
 * <p>To compute the median:
 *
 * {@snippet :
 * double myMedian = median().compute(myDataset);
 * }
 *
 * where {@link #median()} has been statically imported.
 *
 * <p>To compute the 99th percentile:
 *
 * {@snippet :
 * double myPercentile99 = percentiles().index(99).compute(myDataset);
 * }
 *

 *          since this whole object is kept in the classloader between builds.
 *          Anything that changes must be in a val with a get() method that recomputes the value each time.
 */
object BuildEnvironment {

    /**
     * A selection of environment variables injected into the environment by the `codeql-env.sh` script.
     */
    private

    assertEquals(0x388ee898bad75cbfL, hasher.hash().asLong());
  }

  /** Convenience method to compute a fingerprint on a full bytes array. */
  private static long fingerprint(byte[] bytes) {
    return fingerprint(bytes, bytes.length);
  }

  /** Convenience method to compute a fingerprint on a subset of a byte array. */
  private static long fingerprint(byte[] bytes, int length) {

    }

    computedRuntimes {
        client = false
        daemon = false
        worker = false
    }

    // TODO: Most of these properties are the same across projects. We should
    // compute these at the settings-level instead of the project-level.
    identity {
        baseName = "gradle-$name"
        buildTimestamp = buildTimestamp()
        promotionBuild = isPromotionBuild

   * while iteration is in progress.
   *
   * <p>The returned {@code Iterable} can be iterated over multiple times. Every iterator will
   * compute its next element on the fly. It is thus possible to limit the traversal to a certain
   * number of nodes as follows:
   *
   * {@snippet :
   * Iterables.limit(Traverser.forGraph(graph).breadthFirst(node), maxNumberOfNodes);

common:cuda_clang --copt=-Qunused-arguments
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current

        // the value for the key is already being computed.
        computingValueReference = new ComputingValueReference<>(valueReference);

        // Compute the value now, so if it throws an exception we don't change anything.
        newValue = computingValueReference.compute(key, function);

        if (e == null) {
          createNewEntry = true;
          e = newEntry(key, hash, first);