// cause a crash, but because we're running in a separate process
	// it's extremely unlikely.
	runtime.GC()
	runtime.GC()

	// fing will only pick the new IntRegArgs up if it's currently
	// sleeping and wakes up, so wait for it to go to sleep.
	success := false
	for i := 0; i < 100; i++ {
		if runtime.FinalizerGAsleep() {
			success = true
			break
		}
		time.Sleep(20 * time.Millisecond)
	}

	"runtime/asan",
	// We omit bytealg even though it's imported by runtime because it also
	// backs a lot of package bytes. Currently we don't have a way to omit race
	// instrumentation when used from the runtime while keeping race
	// instrumentation when used from user code. Somehow this doesn't seem to
	// cause problems, though we may be skating on thin ice. See #61204.
	"-internal/bytealg",
}

	// The old FD will never be closed, but we are about to crash anyway.
	//
	// On the writeErrData thread, panicking.Add(1) happens-before
	// crashFD.Load() [2].
	//
	// On this thread, swapping old FD for new in crashFD happens-before
	// panicking.Load() > 0.
	//
	// Therefore, if panicking.Load() == 0 here (old FD will be closed), it
	// is impossible for the writeErrData thread to observe

fun <V> Map<String, V>.filterKeysByPrefix(prefix: String): Map<String, V?> =
    filterKeys { key -> key.length > prefix.length && key.startsWith(prefix) }


/**
 * Inverts the given map by swapping its keys with their corresponding values and returns the resulting map.
 *
 * If the original map contains duplicate values, the resulting map will map each value to the key associated

import java.util.concurrent.Callable;

/**
 * Simple guava-based classloader cache. Usually used with a very small size (< 10),
 * as classloaders are strongly referenced.
 *
 * Keeping them strongly referenced allows us to correctly release resources for the evicted entries.
 */
public class GuavaBackedClassLoaderCache<K> implements AutoCloseable {
    private final Cache<K, ClassLoader> cache;

import (
	. "math/rand/v2"
	"testing"
)

// This test is first, in its own file with an alphabetically early name,
// to try to make sure that it runs early. It has the best chance of
// detecting deterministic seeding if it's the first test that runs.

func TestAuto(t *testing.T) {
	// Pull out 10 int64s from the global source
	// and then check that they don't appear in that
	// order in the deterministic seeded result.

    - name: grpc-query
      port: 16685
      protocol: TCP
      targetPort: 16685
  selector:
    app: jaeger
---
# Jaeger implements the Zipkin API. To support swapping out the tracing backend, we use a Service named Zipkin.
apiVersion: v1
kind: Service
metadata:
  labels:
    name: zipkin
  name: zipkin
  namespace: istio-system
spec:
  ports:
    - port: 9411

	recursive    bool       `msg:"rec"`
	dataVersion  uint8      `msg:"v"`
}

func (m *metacache) finished() bool {
	return !m.ended.IsZero()
}

// worthKeeping indicates if the cache by itself is worth keeping.
func (m *metacache) worthKeeping() bool {
	if m == nil {
		return false
	}
	cache := m
	switch {
	case !cache.finished() && time.Since(cache.lastUpdate) > metacacheMaxRunningAge:

      fail<Any>()
    } catch (expected: IOException) {
    }
    server.url("/b").toUrl().openConnection().getInputStream() // Should succeed.
  }

  /**
   * Throttle the request body by sleeping 500ms after every 3 bytes. With a 6-byte request, this
   * should yield one sleep for a total delay of 500ms.
   */
  @Test
  fun throttleRequest() {
    assumeNotWindows()
    server.enqueue(

    val inputStream = server.url("/a").toUrl().openConnection().getInputStream()
    assertThat(inputStream!!.read()).isEqualTo('B'.code)
  }

  /**
   * Throttle the request body by sleeping 500ms after every 3 bytes. With a 6-byte request, this
   * should yield one sleep for a total delay of 500ms.
   */
  @Test
  fun throttleRequest() {
    assumeNotWindows()
    server.enqueue(