}

  /*
   * AbstractCollection fails the removeAll(null) test when the subject
   * collection is empty, but we'd still like to test removeAll(null) when we
   * can. We split the test into empty and non-empty cases. This allows us to
   * suppress only the former.
   */

  @CollectionFeature.Require(SUPPORTS_REMOVE)
  @CollectionSize.Require(ZERO)
  public void testRemoveAll_nullCollectionReferenceEmptySubject() {

import com.google.common.annotations.GwtCompatible;
import java.util.Map;
import org.jspecify.annotations.NonNull;
import org.jspecify.annotations.NullMarked;
import org.jspecify.annotations.Nullable;

/**
 * Test cases for a {@link Table} implementation supporting reads and writes.
 *
 * @author Jared Levy
 * @author Louis Wasserman
 */
@GwtCompatible
@NullMarked
public abstract class AbstractTableTest<C extends @Nullable Character>

        assertEscaping(xmlEscaper, "\uFFFD", ch);
      }
    }

    // Test _all_ allowed characters (including surrogate values).
    for (char ch = 0x20; ch <= 0xFFFD; ch++) {
      // There are a small number of cases to consider, so just do it manually.
      if (ch == '&') {
        assertEscaping(xmlEscaper, "&amp;", ch);
      } else if (ch == '<') {
        assertEscaping(xmlEscaper, "&lt;", ch);
      } else if (ch == '>') {

This also means that in many cases you can pass the same object you get from a request **directly to the database**, as everything is validated automatically.

The same applies the other way around, in many cases you can just pass the object you get from the database **directly to the client**.

 */

package com.google.common.math;

import java.math.BigInteger;
import java.util.Random;
import org.jspecify.annotations.NullUnmarked;

/**
 * Utilities for benchmarks.
 *
 * <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
 * the input itself, so most methods which generate values use an exponential distribution varying

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeoutException;
import junit.framework.TestCase;
import org.jspecify.annotations.NullUnmarked;

/**
 * Test cases for {@link SettableFuture}.
 *
 * @author Sven Mawson
 */
@NullUnmarked
public class SettableFutureTest extends TestCase {

  private SettableFuture<String> future;
  private ListenableFutureTester tester;

/**
 * Tests for SmbFilenameFilter interface behaviors via simple implementations.
 * Each test creates a concrete filter to validate expected contract semantics
 * including normal operation, null handling, edge cases, and exception flow.
 */
@ExtendWith(MockitoExtension.class)
class SmbFilenameFilterTest {

    @Mock
    SmbFile mockDir;

    /**
     * Happy-path: a filter that accepts any name.
     */

    start();
  }

  // Thread.stop() is okay because all threads started by a test are dying at the end of the test,
  // so there is no object state put at risk by stopping the threads abruptly. In some cases a test
  // may put a thread into an uninterruptible operation intentionally, so there is no other way to
  // clean up these threads.
  @SuppressWarnings("deprecation")
  @Override
  public void tearDown() throws Exception {

Write throughput is typically at least 500MB/s per CPU core,
and scales with the number of available CPU cores.
Decompression speed is typically at least 1GB/s.

This means that in cases where raw IO is below these numbers
compression will not only reduce disk usage but also help increase system throughput.
Typically, enabling compression on spinning disk systems
will increase speed when the content can be compressed.