return err
		}
	}
	return nil
}

func runClientTestForVersion(t *testing.T, template *clientTest, version, option string) {
	// Make a deep copy of the template before going parallel.
	test := *template
	if template.config != nil {
		test.config = template.config.Clone()
	}
	test.name = version + "-" + test.name
	test.args = append([]string{option}, test.args...)

		if have59 && !have516 {
			testenv.SkipFlaky(t, 49065)
		}
	}

	// Run a workload in a single goroutine, then run copies of the same
	// workload in several goroutines. For both the serial and parallel cases,
	// the CPU time the process measures with its own profiler should match the
	// total CPU usage that the OS reports.
	//
	// We could also check that increases in parallelism (GOMAXPROCS) lead to a

            configurations {
                conf
            }
        """
        addDependenciesTo(otherBuildFile)
        otherBuildFile << """
            // this is for parallel execution
            checkDeps.mustRunAfter(rootProject.checkDeps)
        """
        given:
        def supplierInteractions = withPerVersionStatusSupplier(file("buildSrc/src/main/groovy/MP.groovy"))

			uniqueTestString := fmt.Sprintf("global-mount-%s", testName)
			uniquePodDir := fmt.Sprintf("%s-%x", kubeletPodsDir, md5.Sum([]byte(uniqueTestString)))
			t.Run(testName+"[", func(t *testing.T) {
				t.Parallel()
				pv := &v1.PersistentVolume{
					ObjectMeta: metav1.ObjectMeta{
						Name: tc.volumeName,
						UID:  "pvuid",
					},
					Spec: v1.PersistentVolumeSpec{

	for i, line := range lines {
		lines[i] = strings.SplitN(line, "] ", 2)[1]
	}
	return lines
}

func TestGetEncryptionConfigHash(t *testing.T) {
	t.Parallel()

	tests := []struct {
		name     string
		filepath string
		wantHash string
		wantErr  string
	}{
		{
			name:     "empty config file content",

    if (op->hasAttr(kXlaOutsideCompilationAttr)) {
      op->removeAttr(
          StringAttr::get(op->getContext(), kXlaOutsideCompilationAttr));
    }
  });
}

// The results of parallel executes is the combination of return values from
// both host and device.
llvm::SmallVector<Type, 4> GetParallelExecuteResultsTypes(
    ArrayRef<Value> return_value_from_host,

			// By parallelizing test cases we ensure that the order in which test cases are defined
			// doesn't automatically preclude some scenarios from happening.
			t.Parallel()

			out := &example.Pod{}
			err := store.Get(ctx, tt.key, storage.GetOptions{IgnoreNotFound: tt.ignoreNotFound, ResourceVersion: tt.rv}, out)
			if tt.expectNotFoundErr {

            <pgp value="91268E187CDC92936DF90106AC01D965C791B637"/>
         </artifact>
      </component>
      <component group="org.scala-lang.modules" name="scala-parallel-collections_2.13" version="0.2.0">
         <artifact name="scala-parallel-collections_2.13-0.2.0.jar">
            <pgp value="C44A68FD10FF456C91E2757D18088D07854014B3"/>
         </artifact>
      </component>

[[checkstyle_worker_api]]
==== Checkstyle tasks use toolchains and execute in parallel by default

The <<checkstyle_plugin.adoc#checkstyle_plugin,Checkstyle plugin>> now uses the Gradle worker API to run Checkstyle as an external worker process.
Multiple Checkstyle tasks may now run in parallel within a project.

// necessarily themselves be in "all". (That configuration does not arise in Go
// 1.11–1.15, but it will be possible in Go 1.16+.)
//
// Loading proceeds from the roots, using a parallel work-queue with a limit on
// the amount of active work (to avoid saturating disks, CPU cores, and/or
// network connections). Each package is added to the queue the first time it is