finalResults.clear();
    }
    executor.shutdown();
  }

  // In a previous implementation this would cause a stack overflow after ~2000 futures chained
  // together.  Now it should only be limited by available memory (and time)
  public void testSetFuture_stackOverflow() {
    SettableFuture<String> orig = SettableFuture.create();
    SettableFuture<String> prev = orig;
    for (int i = 0; i < 100000; i++) {

    }

    private Model interpolateModel(Model model, ModelBuildingRequest request, ModelProblemCollector problems) {
        // save profile activations before interpolation, since they are evaluated with limited scope
        List<Profile> originalProfiles = getProfiles(model);

        Model interpolatedModel =
                modelInterpolator.interpolateModel(model, model.getProjectDirectory(), request, problems);

labels.backup_configuration=Sauvegarde
labels.backup_name=Nom
labels.backup_bulk_file=Fichier en vrac
labels.backup_button_upload=Téléverser
labels.process_time_is_exceeded=Le temps de traitement de la recherche a dépassé la limite. Les résultats affichés peuvent être partiels.
labels.user_given_name=Prénom
labels.givenName=Prénom (nom donné)
labels.user_surname=Nom de famille
labels.surame=Nom de famille
labels.user_mail=E-mail

	// Start by embedding cluster info.
	if b := getClusterMetaInfo(ctx); len(b) > 0 {
		internalLogIf(ctx, embedFileInZip(zipWriter, "cluster.info", b, 0o600))
	}

	// Profiles can be quite big, so we limit to max 16 concurrent downloads.
	ng := WithNPeersThrottled(len(sys.peerClients), 16)
	var writeMu sync.Mutex
	for i, client := range sys.peerClients {
		if client == nil {
			continue
		}

		Hidden: true,
		EnvVar: "MINIO_CROSSDOMAIN_XML",
	},
	cli.StringFlag{
		Name:   "memlimit",
		Usage:  "set global memory limit per server via GOMEMLIMIT",
		Hidden: true,
		EnvVar: "MINIO_MEMLIMIT",
	},
	cli.IntFlag{
		Name:   "send-buf-size",
		Value:  4 * humanize.MiByte,
		EnvVar: "MINIO_SEND_BUF_SIZE",
		Hidden: true,
	},

recommended to configure the IDE to initiate multiple listening attempts. In case of IntelliJ, this option
is called "Auto restart" and needs to be checked. In case of Eclipse, "Connection limit" setting
needs to be configured with a greater value (ie 10 or more).

NOTE: If you have imported the project into IntelliJ according to the instructions in

	if err != nil {
		return result, toObjectErr(err, bucket, object, uploadID)
	}

	uploadIDPath := er.getUploadIDDir(bucket, object, uploadID)
	if partNumberMarker < 0 {
		partNumberMarker = 0
	}

	// Limit output to maxPartsList.
	if maxParts > maxPartsList {
		maxParts = maxPartsList
	}

	// Populate the result stub.
	result.Bucket = bucket
	result.Object = object
	result.UploadID = uploadID

    List<@Nullable Integer> list2 = Lists.newArrayList(1);
    List<@Nullable Integer> list3 = Lists.newArrayList(1, 1);
    List<@Nullable Integer> list4 = Lists.newArrayList(1, 2);
    List<@Nullable Integer> list5 = Lists.newArrayList(1, null, 2);
    List<@Nullable Integer> list6 = Lists.newArrayList(2);
    List<@Nullable Integer> list7 = Lists.newArrayList(nullInt);

    List<@Nullable Integer> list2 = Lists.newArrayList(1);
    List<@Nullable Integer> list3 = Lists.newArrayList(1, 1);
    List<@Nullable Integer> list4 = Lists.newArrayList(1, 2);
    List<@Nullable Integer> list5 = Lists.newArrayList(1, null, 2);
    List<@Nullable Integer> list6 = Lists.newArrayList(2);
    List<@Nullable Integer> list7 = Lists.newArrayList(nullInt);

    int ntasks = tasks.size();
    checkArgument(ntasks > 0);
    List<Future<T>> futures = Lists.newArrayListWithCapacity(ntasks);
    BlockingQueue<Future<T>> futureQueue = Queues.newLinkedBlockingQueue();
    long timeoutNanos = unit.toNanos(timeout);

    // For efficiency, especially in executors with limited
    // parallelism, check to see if previously submitted tasks are