}
		return nil
	}
	// First walk the base modules that must be listed.
	var min []module.Version
	haveBase := map[string]bool{}
	for _, path := range base {
		if haveBase[path] {
			continue
		}
		m := module.Version{Path: path, Version: max[path]}
		min = append(min, m)
		walk(m)
		haveBase[path] = true
	}
	// Now the reverse postorder to bring in anything else.
	for i := len(postorder) - 1; i >= 0; i-- {

 *       <ul>
 *         <li>2 levels: average of 64ns per lock()/unlock()
 *         <li>3 levels: average of 77ns per lock()/unlock()
 *         <li>4 levels: average of 99ns per lock()/unlock()
 *         <li>5 levels: average of 103ns per lock()/unlock()
 *         <li>10 levels: average of 184ns per lock()/unlock()
 *         <li>20 levels: average of 393ns per lock()/unlock()
 *       </ul>
 * </ul>
 *

			// (When we do a lifo insertion, we preserve this property by
			// copying the old head's acquiretime into the inserted new head.
			// In that case the overall average may be slightly high, but that's fine:
			// the average of the ends is only an approximation to the actual
			// average anyway.)
			// The root.dequeue above changed the head and tail acquiretime
			// to the current time, so the next unlock will not re-count this contention.

	// O(n lg n) time.  Fortunately, the checkLinear test
	// leaves enough wiggle room to include n lg n time
	// (it actually tests for O(n^log_2(3)).
	// To prevent false positives, average away variation
	// by doing multiple rounds within a single run.
	checkLinear("iterdelete", 2500, func(n int) {
		for round := 0; round < 4; round++ {
			m := map[int]int{}
			for i := 0; i < n; i++ {
				m[i] = i

            if (workerCount > 0) {
                LOGGER.lifecycle("average select time: " + format(stats -> stats.totalSelectTime));
                LOGGER.lifecycle("average execute time: " + format(stats -> stats.totalExecuteTime));
                LOGGER.lifecycle("average finish time: " + format(stats -> stats.totalMarkFinishedTime));
            }
            completedWorkers.clear();

		"Divide all samples values by a constant, eg the number of processors or jobs."),
	"mean": helpText(
		"Average sample value over first value (count)",
		"For memory profiles, report average memory per allocation.",
		"For time-based profiles, report average time per event."),
	"sample_index": helpText(
		"Sample value to report (0-based index or name)",
		"Profiles contain multiple values per sample.",

   * MultimapBuilder.hashKeys(expectedKeys).arrayListValues(expectedValuesPerKey).build()}.
   *
   * @param expectedKeys the expected number of distinct keys
   * @param expectedValuesPerKey the expected average number of values per key
   * @throws IllegalArgumentException if {@code expectedKeys} or {@code expectedValuesPerKey} is
   *     negative
   */
  public static <K extends @Nullable Object, V extends @Nullable Object>

  // We could make this a Map<E, EndpointPair<N>>. It would make incidentNodes(edge) slightly
  // faster, but also make Networks consume 5 to 20+% (increasing with average degree) more memory.
  final MapIteratorCache<E, N> edgeToReferenceNode; // referenceNode == source if directed

  /** Constructs a graph with the properties specified in {@code builder}. */

  // We could make this a Map<E, EndpointPair<N>>. It would make incidentNodes(edge) slightly
  // faster, but also make Networks consume 5 to 20+% (increasing with average degree) more memory.
  final MapIteratorCache<E, N> edgeToReferenceNode; // referenceNode == source if directed

  /** Constructs a graph with the properties specified in {@code builder}. */

   * MultimapBuilder.hashKeys(expectedKeys).arrayListValues(expectedValuesPerKey).build()}.
   *
   * @param expectedKeys the expected number of distinct keys
   * @param expectedValuesPerKey the expected average number of values per key
   * @throws IllegalArgumentException if {@code expectedKeys} or {@code expectedValuesPerKey} is
   *     negative
   */
  public static <K extends @Nullable Object, V extends @Nullable Object>