Memory management in NativeScript for Android

Note: This post will be a bit different from the previous ones. It’s intended to provide brief history as to why current NativeScript for Android implementation is designed this way. So, this post will be most useful for my Telerik ex-colleagues. Think of it as kind of historic documentation. Also, it is a chance to have a peek inside a developer’s mind šŸ˜‰

I already gave you a hint about my current affairs. Since February I took the opportunity to pursue new ventures in a new company. The fact that my new office is the very next building to Telerik HQ gives me an opportunity to keep close connections with my former colleagues. At one such coffee break I was asked about the current memory management implementation. As I am no longer with Telerik, my former colleagues miss some important history that explains why this feature is implemented this way. I tried to explain briefly that particular technical issue in a previous post, however I couldn’t go much in depth because NativeScript was not announced yet. So, here I’ll try to provide more details.

Note: Keep in my that this post is about NativeScript for Android platform, so I will focus only on that platform.

On the very first day of the project, we decided that we should explore what can be done with JavaScript-to-Java bidirectional marshalling. So, we set up a simple goal: make an app with a single button that increments a counter. Let’s see what Android docs says about button widget.

 public class MyActivity extends Activity {
     protected void onCreate(Bundle savedInstanceState) {


         final Button button = findViewById(;
         button.setOnClickListener(new View.OnClickListener() {
             public void onClick(View v) {
                 // Code here executes on main thread after user presses button

After so many years, this is the first code fragment you see on the site. And it should be so. This code fragments captures the very essence of what button widget is and how it is used. We wanted to provide JavaScript syntax which feels familiar to Java developers. So, we ended up with the following syntax:

var button = new android.widget.Button(context);
button.setOnClickListener(new android.view.View.OnClickListener({
   onClick: function() {
      // do some work

This example is shown countless times in NativeScript docs and various presentation slides/materials. It is part of our first and main test/demo app.

Motivation: we wanted to provide JavaScript syntax which is familiar to existing Android developers.

This decision brings an important implication, namely the usage of JavaScript closures. To understand why closures are important for the implementation, we could take a look at the following simple, but complete, Java example.

package com.example;

import android.os.Bundle;
import android.view.View;
import android.widget.Button;
import android.widget.LinearLayout;
import android.widget.TextView;

public class MyActivity extends Activity {
    private int count = 0;

    protected void onCreate(Bundle savedInstanceState) {

        LinearLayout layout = new LinearLayout(this);

        final TextView txt = new TextView(this);

        Button btn = new Button(this);
        btn.setOnClickListener(new View.OnClickListener() {
            public void onClick(View view) {
                txt.setText("Count:" + (++count));


Behind the scene, the Java compiler will generate anonymous class that we can decompile and inspect closely. For the purpose of this post I am going to useĀ fernflower decompiler. Here is the output for MyActivity$1 class.

package com.example;

import android.view.View;
import android.view.View.OnClickListener;
import android.widget.TextView;

class MyActivity$1 implements OnClickListener {
   // $FF: synthetic field
   final TextView val$txt;
   // $FF: synthetic field
   final MyActivity this$0;

   MyActivity$1(MyActivity this$0, TextView var2) {
      this.this$0 = this$0;
      this.val$txt = var2;

   public void onClick(View view) {
      this.val$txt.setText("Count:" + MyActivity.access$004(this.this$0));

We can see the Java compiler generates code that:
1) captures the variable txt
2) deals with ++count expression

This means that the click handler object holds references to the objects it accesses in its closure. We can call this class stateful as it has class members. Fairly trivial observation.

Let’s take a look again at the previous JavaScript code.

var button = new android.widget.Button(context);
button.setOnClickListener(new android.view.View.OnClickListener({
   onClick: function() {
      // do some work

We access the button widget and call itsĀ setOnClickListener method with some argument. This means that we should have instantiate Java object which implementsĀ OnClickListener so that the button can use it later. You can find the class implementation for that object in your project platform directory


Let’s see what the actual implementation is.


public class View_OnClickListener
       implements android.view.View.OnClickListener {
  public View_OnClickListener() {

  public void onClick(android.view.View param_0)  {
    java.lang.Object[] args = new java.lang.Object[1];
    args[0] = param_0;
    com.tns.Runtime.callJSMethod(this, "onClick", void.class, args);

As we can see this class acts as a proxy and doesn’t have fields. We can call this class stateless. We don’t store information that we can use to describe its closure if any.

So, we saw that Java compiler generates classes that keep track of their closures while NativeScript generates classes that don’t keep track of their closures. This is a simple implication due to the fact the JavaScript is a dynamic language and the information of lexical scope is not enough to provide full static analysis. The full information about JavaScript closures can be obtain at run time only.

The ovalsĀ diagram I used in my previous post visualize the missing object reference to the closed object. So, now we have understanding what happens in NativeScript runtime for Android.Ā The current NativeScript, at the time of writing version 3.3, provides mechanism to “compensate” for the missing object references. To put it simply, for each JavaScript closure accessible from Java we traverse all reachable Java objects in order to keep them alive until the closure becomes unreachable from Java. Well, while we were able to describe the current solution in a single sentence it doesn’t mean it doesn’t have drawbacks. This solution could be very slow if an object with large hierarchy, like global, is reachable from some closure. If this is the case, the implication is that we will traverse the whole V8 heap on each GC.

Back then in 2014, when we hit this issue for the first time, we discussed the option to customize part of the V8 garbage collector in order to provide faster heap traversing. The drawback is slower upgrade cycle for V8 which means that JavaScriptCore engine will provide more features at given point in time. For example, it is not easy to explain to the developers why they can use class syntax for iOS but not for Android.

Motivation: we wanted to keep V8 customization at minimum so we can achieve relatively feature parity by upgrading V8 engine as soon as possible.

So, now we know traversing V8 heap can be slow, what else? The current implementation is incomplete and case-by-case driven. This means that it is updated when there are important and common memory usage patterns. For example, currently we don’t traverse Map and Set objects.

Let’s see what can happen in practice. Create a default app.

tns create app1

Run the app and make sure it works as expected.

Now, we have to go through the process of designing a user scenario where the runtime will crash. We know that the current implementation doesn’t traverse Map and Set objects. So, we have to make Java object which is reachable only through, let’s say, Map object. This is only the first part of our exercise. We also must take care to make it reachable through a closure. Finally, we must give a chance for GC to collect it before we use it. So, let’s code it.

function crash() {
    var m = new Map();
    m.set('o', new java.lang.Object() /* via the map only */);
    var h = new android.os.Handler(android.os.Looper.getMainLooper()); java.lang.Runnable({
        run: function() {

That’s all. Finally, we have to integrate crash within our application. We can do so by modifying onTap handler in [proj_dir]/app/main-view-model.js as follows:

viewModel.onTap = function() {
    this.set("message", getMessage(this.counter));

Run the app and click the button. You should get error screen similar to the following one.

Motivation: we wanted to evolve V8 heap traversing on case-by-case basis in order to traverse as little as possible.

Understanding this memory usage pattern (create object, set up object reachability, GC and usage) is a simple but powerful tool. With the current implementation the fix for Map and Set is similar to this one. Also, realizing that the missing references to the closed objects is the only reason for this error with the current implementation is critical for any further changes. This is well documented in the form of unit tests.

So far we discussed the drawbacks of the current implementation. Let’s say a few words about its advantages. First, and foremost, it keeps the current memory management model familiar to the existing Java and JavaScript developers. This is important in order to attract new developers. If two technologies, X and Y, solve similar problems and offer similar licenses, tools, etc., the developers are in favor for the one with simpler “mental model”. While introducing alloc/free or try/finallyĀ approach is powerful, it does not attract new developers because it sets higher entry level, less explicit approach. Another advantage, which is mostly for the platform developers, is the fact that current approach aligns well with many optimizations that can be applied. For example, taking advantage (introducing) of GC generations for the means of NativeScript runtime. Also, it allows per-application fine tuning of existing V8 flags (e.g,Ā gc_interval,Ā incremental_marking,Ā minor_mc, etc.). Tweaking V8 flags won’t have general impact when manual memory management is applied. In my opinion, tuning these flags is yet another way to help regular Joe shooting himself in the foot, but providing same defaults and applying adaptive schemes very possible could be a huge win.

It is important to note that whatever approach is applied, this must be done carefully because of the risk of OOM exception. Introducing schemes like GC generation should consider the object memory weight. This will make obsolete the current approaches that use time and/or memory pressure heuristics. In general, such GC generation approach will pay off well.

I hope I shed more light on this challenging problem. Looking forward to see how the team is going to approach it. Good luck!

Synchronizing GC in Java and V8

In the last post I wrote that I work on a project that involves a lot of interoperability between Java and V8 JavaScript engine. Here is an interesting problem I was investigating the last couple of days.

Both V8 and JVM use garbage collector for memory management. While using GC provides a lot of benefits sometimes having two garbage collectors in a single process can be tricky though. Suppose we have a super-charged version of LiveConnect where we have access to the full Java API.

var file = new"readme.txt");

console.log("length=" + file.length());

These two lines of JavaScript may seem quite simple at first glance. We create an instance of and call one of its methods. The tricky part is that we are doing this from JavaScript and we must take care that the actual Java instance would not be GC’ed before we callĀ length method. In other words, we should provide some form of memory management. Suppose we decide to use JNI global references and we call NewGlobalRef every time when we create a new Java object from JavaScript. Accordingly we call DeleteGlobalRef when V8 makes Java object unreachable from JavaScript.

Let’s see a more complicated scenario.

var outStream = new"log.txt");

var eventCallback = new com.example.EventCallback({
    onDataReceived: function(data) {

var listener = new com.example.EventListener(eventCallback);

In this case we create an instance of com.example.EventCallback and provide its implementation in JavaScript. Now suppose that all these three JavaScript objects become unreachable and V8 is ready to GC them. Just because all of these objects are unreachable in JavaScript it does not mean that their actual counterparts in Java are unreachable. It’s possible that listener and eventCallback objects are still reachable through a stack of a listener Java thread.


Now comes the interesting detail. While in JavaScript eventCallback has a reference to outStream through the function onDataReceived there is no such reference in Java and it is legitimate for Java GC to collect outStream object. The next time when the callback object calls write method there won’t be a corresponding Java object and the application will fail.

There are several solutions to this problem. One of them is to maintain the reachability in Java GC heap graph in sync with the one in JavaScript. After all, if there is an edge connecting eventCallback and outStream Java GC won’t try to collect the latter.

There are two options:

  • sync Java heap graph automatically
  • sync Java heap graph manually

As usual there is a trade-off. While the first option is very desirable there is a price to pay. We should analyze every closure in V8 that is GC’ed and traverse all objects reachable from there. This could slow down the GC by orders of magnitude.

The second option also has drawbacks. In general, JavaScript developers are not used to manual memory management. Introducing new memory management API could cause a lot of discomfort to the less experienced JavaScript developers.

scope(eventCallback, outStream);

Event if we make the API nice and simple, there is a burden of the mental model that JavaScript developers have to maintain. I tend to prefer this option though because many C/C++ developers proved it is possible to build high quality software using manual memory management.

In closing I would say that there are other solutions to this problem. I’ll discuss them in another blog post.

Java and V8 Interoperability

The project I currently work on involves a lot of Java/JavaScript (V8 JavaScript engine) interoperability. Fortunately, Java provides JNI and V8 has a nice C++ API which make the integration process very smooth. Most of the Java-JNI-V8 type marshaling is quite straightforward but there is one exception.

The JNI uses modified UTF-8 strings to represent various string types. Modified UTF-8 strings are the same as those used by the Java VM. Modified UTF-8 strings are encoded so that character sequences that contain only non-null ASCII characters can be represented using only one byte per character, but all Unicode characters can be represented.

I was well aware of this fact since the beginning of the project but somehow I neglected it. Until recently, when one of my colleagues showed me a peculiar bug that turned out to be related to the process of marshaling a non-trivial Unicode string.

At first, I tried a few quick and dirty workarounds just to prove that the root of problem is more complex it seemed. Then I realized that jstring type is not the best type when it comes to string interoperability with V8 engine. I decided to use jbyteArray type instead of jstring though I had some concerns about the performance overhead.

private static native void doSomething(byte[] strData);

String s = "some string";
byte[] strData = s.getBytes("UTF-8");

The code doesn’t look ugly though the string version looks better. I did microbenchmarks and it turned out the performance is good enough for my purposes. Nevertheless, I decided to compare the performance with Nashorn JavaScript engine. As expected, Nashorn implementation was faster because it uses the same internal string format as the JVM.