import static com.google.common.collect.Maps.uniqueIndex;

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import com.google.caliper.api.Footprint;
import com.google.common.collect.BenchmarkHelpers.BiMapImpl;
import com.google.common.collect.BenchmarkHelpers.MapImpl;
import com.google.common.collect.BenchmarkHelpers.MapsImplEnum;

import com.google.caliper.AfterExperiment;
import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import com.google.caliper.api.Footprint;
import com.google.caliper.api.VmOptions;
import java.util.HashSet;
import java.util.Set;
import java.util.concurrent.Executor;
import java.util.concurrent.atomic.AtomicInteger;

/**

import com.google.caliper.AfterExperiment;
import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import com.google.caliper.api.Footprint;
import com.google.caliper.api.VmOptions;
import java.util.HashSet;
import java.util.Set;
import java.util.concurrent.Executor;
import java.util.concurrent.atomic.AtomicInteger;

/**

 *   <li>Access to all collection-based utilities via {@link #asList} (though at the cost of
 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code int[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).
 *   <li><i>Some</i> construction use cases force the data to be copied (though several construction
 *       APIs are offered that don't).

import com.google.caliper.AfterExperiment;
import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import com.google.caliper.api.Footprint;
import com.google.caliper.api.VmOptions;
import com.google.common.base.Preconditions;
import com.google.common.collect.Lists;
import com.google.common.util.concurrent.AbstractFutureBenchmarks.OldAbstractFuture;

 *   <li>Access to all collection-based utilities via {@link #asList} (though at the cost of
 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code double[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).
 *   <li><i>Some</i> construction use cases force the data to be copied (though several construction
 *       APIs are offered that don't).

import com.google.caliper.AfterExperiment;
import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import com.google.caliper.api.Footprint;
import com.google.caliper.api.VmOptions;
import com.google.common.base.Preconditions;
import com.google.common.collect.Lists;
import com.google.common.util.concurrent.AbstractFutureBenchmarks.OldAbstractFuture;

    bulkGetSet = ImmutableList.copyOf(limit(cycle(asList), 10));
  }

  @Footprint
  Object sizeOfStriped() {
    return impl.get(numStripes);
  }

  // a place to put the locks in sizeOfPopulatedStriped so they don't get GC'd before we measure
  final List<Lock> locks = new ArrayList<>(numStripes);

  @Footprint
  Object sizeOfPopulatedStriped() {
    locks.clear();

    bulkGetSet = ImmutableList.copyOf(limit(cycle(asList), 10));
  }

  @Footprint
  Object sizeOfStriped() {
    return impl.get(numStripes);
  }

  // a place to put the locks in sizeOfPopulatedStriped so they don't get GC'd before we measure
  final List<Lock> locks = new ArrayList<>(numStripes);

  @Footprint
  Object sizeOfPopulatedStriped() {
    locks.clear();

 * lock, but also maximizes memory footprint. On the other extreme, one could use a single lock for
 * all tasks, which minimizes memory footprint but also minimizes concurrency. Instead of choosing
 * either of these extremes, {@code Striped} allows the user to trade between required concurrency
 * and memory footprint. For example, if a set of tasks are CPU-bound, one could easily create a