@Param({"3", "30", "300"})
  int count;

  @Param({"0", "1", "16", "32", "100"})
  int componentLength;

  private Iterable<String> components;

  @BeforeExperiment
  void setUp() {
    String component = Strings.repeat("a", componentLength);
    String[] raw = new String[count];
    Arrays.fill(raw, component);
    components = Arrays.asList(raw);
  }

    @TempDir
    Path tempDir;

    private final DefaultProfileActivationContext context = new DefaultProfileActivationContext();

    @BeforeEach
    @Override
    void setUp() throws Exception {
        activator = new FileProfileActivator(
                new ProfileActivationFilePathInterpolator(new DefaultPathTranslator(), bd -> true));

        context.setProjectDirectory(tempDir.toFile());

/**
 * Tests {@link PropertyProfileActivator}.
 *
 */
class PropertyProfileActivatorTest extends AbstractProfileActivatorTest<PropertyProfileActivator> {

    @BeforeEach
    @Override
    void setUp() throws Exception {
        activator = new PropertyProfileActivator();
    }

    private Profile newProfile(String key, String value) {
        ActivationProperty ap =

Cuanto más sencillo sea el problema resuelto por la herramienta, mejor rendimiento obtendrá. Y la mayoría de los benchmarks no prueban las funciones adicionales proporcionadas por la herramienta.

La jerarquía sería:

* **Uvicorn**: como servidor ASGI
    * **Starlette**: (usa Uvicorn) un microframework web

        if (jobLogPager.id != null) {
            cb.query().docMeta().setId_Equal(jobLogPager.id);
        }
        // TODO Long, Integer, String supported only.

        // setup condition
        cb.query().addOrderBy_StartTime_Desc();
        cb.query().addOrderBy_EndTime_Desc();

        // search

    }

    public void deleteBefore(final int days) {

        if (scheduledJobPager.id != null) {
            cb.query().docMeta().setId_Equal(scheduledJobPager.id);
        }
        // TODO Long, Integer, String supported only.

        // setup condition
        cb.query().addOrderBy_SortOrder_Asc();
        cb.query().addOrderBy_Name_Asc();

        // search

    }

    public List<ScheduledJob> getScheduledJobList() {

        if (userPager.id != null) {
            cb.query().docMeta().setId_Equal(userPager.id);
        }
        // TODO Long, Integer, String supported only.

        // setup condition
        cb.query().addOrderBy_Name_Asc();

        // search

    }

    public List<User> getAvailableUserList() {
        return userBhv.selectList(cb -> {

  ByteSinkTester(
      ByteSinkFactory factory, byte[] data, String suiteName, String caseDesc, Method method) {
    super(factory, data, suiteName, caseDesc, method);
  }

  @Override
  protected void setUp() throws Exception {
    sink = factory.createSink();
  }

  public void testOpenStream() throws IOException {
    OutputStream out = sink.openStream();
    try {

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);
  static AtomicLong misses = new AtomicLong(0);

  @BeforeExperiment
  void setUp() {
    // random integers will be generated in this range, then raised to the
    // power of (1/concentration) and floor()ed
    max = Ints.checkedCast((long) Math.pow(distinctKeys, concentration));

    cache =

  private static final int[] slowFactorials = new int[ARRAY_SIZE];
  private static final int[] binomials = new int[ARRAY_SIZE];

  @Param({"50", "1000", "10000"})
  int factorialBound;

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      factorials[i] = RANDOM_SOURCE.nextInt(factorialBound);
      slowFactorials[i] = RANDOM_SOURCE.nextInt(factorialBound);