import java.util.Map;
import java.util.Map.Entry;
import org.checkerframework.checker.nullness.qual.Nullable;
import org.junit.Ignore;

/**
 * Base class for map testers.
 *
 * <p>TODO: see how much of this is actually needed once Map testers are written. (It was cloned
 * from AbstractCollectionTester.)
 *
 * @param <K> the key type of the map to be tested.
 * @param <V> the value type of the map to be tested.

  <url>https://github.com/google/guava</url>
  <description>
    Guava is a suite of core and expanded libraries that include
    utility classes, Google's collections, I/O classes, and
    much more.
  </description>
  <dependencies>
    <dependency>
      <groupId>com.google.guava</groupId>
      <artifactId>failureaccess</artifactId>
      <version>1.0.2</version>
    </dependency>
    <dependency>

import java.util.Map;
import java.util.Map.Entry;
import org.checkerframework.checker.nullness.qual.Nullable;
import org.junit.Ignore;

/**
 * Base class for map testers.
 *
 * <p>TODO: see how much of this is actually needed once Map testers are written. (It was cloned
 * from AbstractCollectionTester.)
 *
 * @param <K> the key type of the map to be tested.
 * @param <V> the value type of the map to be tested.

   * we've chosen to instead use a signature that benefits existing users -- and is still safe.
   *
   * For convertAll, I haven't looked as closely at *how* much existing users benefit, so we should
   * keep an eye out for problems that new users encounter. Note also that convertAll could support
   * both use cases by using @PolyNull. (By contrast, we can't use @PolyNull for our superinterface

   * to reduce cache contention on most processors. Padding is
   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each
   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without
   * this precaution.

   * to reduce cache contention on most processors. Padding is
   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each
   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without
   * this precaution.

  <url>https://github.com/google/guava</url>
  <description>
    Guava is a suite of core and expanded libraries that include
    utility classes, Google's collections, I/O classes, and
    much more.
  </description>
  <dependencies>
    <dependency>
      <groupId>com.google.guava</groupId>
      <artifactId>failureaccess</artifactId>
      <version>1.0.2</version>
    </dependency>
    <dependency>

    return -1;
  }

  /**
   * Returns the start position of the first occurrence of the specified {@code target} within
   * {@code array}, or {@code -1} if there is no such occurrence.
   *
   * <p>More formally, returns the lowest index {@code i} such that {@code Arrays.copyOfRange(array,
   * i, i + target.length)} contains exactly the same elements as {@code target}.
   *

   *
   * <p><i>Performance notes:</i> while the cartesian product of lists of size {@code m, n, p} is a
   * list of size {@code m x n x p}, its actual memory consumption is much smaller. When the
   * cartesian product is constructed, the input lists are merely copied. Only as the resulting list
   * is iterated are the individual lists created, and these are not retained after iteration.
   *

   * we've chosen to instead use a signature that benefits existing users -- and is still safe.
   *
   * For convertAll, I haven't looked as closely at *how* much existing users benefit, so we should
   * keep an eye out for problems that new users encounter. Note also that convertAll could support
   * both use cases by using @PolyNull. (By contrast, we can't use @PolyNull for our superinterface